Can you write a warm but technical and long text? Say a few paragraphs


⚪ Received
Stage: queued for agent
Model: openrouter/deepseek/deepseek-v4-flash
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 4t)
Ctx: est 3.0k/1.0M; provider 27.9k
Turn: i 27.9k o 34 t 26 billed $0.0115


* ⚪ Queued
Stage: waiting for conversation turn
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 0.0s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 4t)
Ctx: est 3.0k/1.0M; provider 27.9k
Turn: i 27.9k o 34 t 26 billed $0.0115


* 🟡 Working
Stage: building prompt
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 0.3s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 4t)
Ctx: est 3.0k/1.0M; provider 27.9k
Turn: i 27.9k o 34 t 26 billed $0.0115


* 🟡 Working
Stage: model running
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 0.5s
Time: overhead 0.5s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 4t)
Turn: i 27.9k o 34 t 26 billed $0.0115; p≈283tok/1.1kch
Ctx: est 3.0k/1.0M; provider 27.9k


* 🟡 Working
Stage: model running
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 5.8s
Time: model 5.0s, overhead 0.5s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 4t)
Turn: i 27.9k o 34 t 26 billed $0.0115; p≈283tok/1.1kch
Ctx: est 3.0k/1.0M; provider 27.9k


* 🟡 Working
Stage: model running
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 11.0s
Time: model 10.2s, overhead 0.5s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 5t)
Turn: i 27.9k o 34 t 26 billed $0.0115; p≈283tok/1.1kch
Ctx: est 3.7k/1.0M; provider 27.9k


* 🟡 Processing result
Stage: model returned
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 12.4s
Time: model 11.6s, overhead 0.5s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 5t)
Turn: i 28.3k o 420 t 89 billed $0.0148; p≈283tok/1.1kch
Ctx: est 3.8k/1.0M; provider 28.3k


There's something quietly magical about what happens when you press the power button on a computer. In that first instant, voltage rails ramp up under the watchful eye of the power-good signal. The CPU, still groggy, begins executing instructions at the reset vector — a fixed address hardwired into silicon, etched during fabrication years ago in a clean room halfway around the world. What follows is a chain of trust: microcode patches, cache initialization, memory controller training, POST. Every single transistor waking up in sequence, like an orchestra tuning before the concert begins. The engineers who wrote that bootstrap code may have moved on to other projects, but their logic lives on, faithfully replayed billions of times.

Then the kernel takes over. Virtual memory paging tables are constructed, interrupt descriptors are laid out in memory, scheduler runqueues are initialized. The system begins managing resources — not because anyone told it to this time around, but because the code paths were hardened over decades of iteration. Device drivers probe for hardware they may or may not find: a controller enumerates the PCI bus, an AHCI driver checks for SATA links, network cards negotiate link speeds. Each probe is a conversation between software and physics. Some devices respond, some don't. Either way, the kernel handles it gracefully. There's a resilience in that — it took thousands of developer-years to make failure feel this routine.

And finally, the init system spawns userspace. `systemd` (or your init of choice) fans out dependencies, starts dbus, logs in. You get a prompt, a desktop, or a web server accepting requests. The machine, for all its staggering complexity — from quantum tunneling in doped silicon to the TCP stack's congestion control — settles into service. It's just sitting there, waiting for your next thought. The warmth I find in this is simple: all that intricate, layered effort exists to amplify one person's intent into action. That's remarkable engineering, and it never gets old.


* 🟢 Done
Stage: final reply sent
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 12.6s
Time: model 11.6s, overhead 1.0s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 5t)
Turn: i 28.3k o 420 t 89 billed $0.0148; p≈283tok/1.1kch
Ctx: est 3.8k/1.0M; provider 28.3k


This is a good text thanks


⚪ Received
Stage: queued for agent
Model: openrouter/deepseek/deepseek-v4-flash
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 5t)
Ctx: est 3.8k/1.0M; provider 28.3k
Turn: i 28.3k o 420 t 89 billed $0.0148


* ⚪ Queued
Stage: waiting for conversation turn
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 0.0s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 5t)
Ctx: est 3.8k/1.0M; provider 28.3k
Turn: i 28.3k o 420 t 89 billed $0.0148


* 🟡 Working
Stage: building prompt
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 0.3s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 5t)
Ctx: est 3.8k/1.0M; provider 28.3k
Turn: i 28.3k o 420 t 89 billed $0.0148


* 🟡 Working
Stage: model running
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 0.6s
Time: overhead 0.6s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 5t)
Turn: i 28.3k o 420 t 89 billed $0.0148; p≈587tok/2.3kch
Ctx: est 3.8k/1.0M; provider 28.3k


* 🟡 Working
Stage: model running
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 5.8s
Time: model 5.0s, overhead 0.6s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 5t)
Turn: i 28.3k o 420 t 89 billed $0.0148; p≈587tok/2.3kch
Ctx: est 3.8k/1.0M; provider 28.3k


* 🟡 Processing result
Stage: model returned
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 7.9s
Time: model 7.1s, overhead 0.6s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 6t)
Turn: i 29.3k o 26 t 15 billed $0.0181; p≈587tok/2.3kch
Ctx: est 4.4k/1.0M; provider 29.3k


You're welcome! Glad you enjoyed it. :)


* 🟢 Done
Stage: final reply sent
Model: openrouter/deepseek/deepseek-v4-flash
Elapsed: 8.1s
Time: model 7.1s, overhead 1.0s
Backend: ses_1bd795428ffeyh5q5oD9ZmG71F (since 05-20 01:16 CEST, 6t)
Turn: i 29.3k o 26 t 15 billed $0.0181; p≈587tok/2.3kch
Ctx: est 4.4k/1.0M; provider 29.3k


Test


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 62t)
Ctx: est 132.4k/200.0k; warn 160.0k reload 190.0k; provider 275.9k
Turn: i 333 o 456 t 402 cache 275.6k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 62t)
Ctx: est 132.4k/200.0k; warn 160.0k reload 190.0k; provider 275.9k
Turn: i 333 o 456 t 402 cache 275.6k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 62t)
Ctx: est 132.4k/200.0k; warn 160.0k reload 190.0k; provider 275.9k
Turn: i 333 o 456 t 402 cache 275.6k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.6s
Time: overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 62t)
Turn: i 333 o 456 t 402 cache 275.6k; p≈1.0ktok/4.1kch
Ctx: est 132.4k/200.0k; warn 160.0k reload 190.0k; provider 275.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.3s
Time: model 5.0s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 62t)
Turn: i 333 o 456 t 402 cache 275.6k; p≈1.0ktok/4.1kch
Ctx: est 132.4k/200.0k; warn 160.0k reload 190.0k; provider 275.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 13.0s
Time: model 10.7s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 63t)
Turn: i 21.4k o 19 t 39 cache 262.1k; p≈1.0ktok/4.1kch
Ctx: est 133.4k/200.0k; warn 160.0k reload 190.0k; provider 283.5k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 13.9s
Time: model 11.6s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 63t)
Turn: i 21.4k o 19 t 39 cache 262.1k; p≈1.0ktok/4.1kch
Ctx: est 133.4k/200.0k; warn 160.0k reload 190.0k; provider 283.5k


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 14.6s
Time: model 11.6s, overhead 3.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 63t)
Turn: i 21.4k o 19 t 39 cache 262.1k; p≈1.0ktok/4.1kch
Ctx: est 133.4k/200.0k; warn 160.0k reload 190.0k; provider 283.5k


It's me this time


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 63t)
Ctx: est 133.4k/200.0k; warn 160.0k reload 190.0k; provider 283.5k
Turn: i 21.4k o 19 t 39 cache 262.1k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 63t)
Ctx: est 133.4k/200.0k; warn 160.0k reload 190.0k; provider 283.5k
Turn: i 21.4k o 19 t 39 cache 262.1k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 63t)
Ctx: est 133.4k/200.0k; warn 160.0k reload 190.0k; provider 283.5k
Turn: i 21.4k o 19 t 39 cache 262.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.4s
Time: overhead 1.4s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 63t)
Turn: i 21.4k o 19 t 39 cache 262.1k; p≈697tok/2.8kch
Ctx: est 133.4k/200.0k; warn 160.0k reload 190.0k; provider 283.5k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.2s
Time: model 5.0s, overhead 1.4s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 63t)
Turn: i 21.4k o 19 t 39 cache 262.1k; p≈697tok/2.8kch
Ctx: est 133.4k/200.0k; warn 160.0k reload 190.0k; provider 283.5k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 12.5s
Time: model 10.3s, overhead 1.4s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 64t)
Turn: i 915 o 95 t 60 cache 283.4k; p≈697tok/2.8kch
Ctx: est 134.2k/200.0k; warn 160.0k reload 190.0k; provider 284.3k


Hey, you're back. The session had a rough patch with timeouts there — sorry about that. The 110K+ context with heavy tool calls might be hitting Kimi's processing limits on certain turns.

We were talking about the handover discovery problem (how would I know to grep at session start without being told). Want to pick that back up, or shift gears to something else?


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 13.3s
Time: model 10.3s, overhead 3.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 64t)
Turn: i 915 o 95 t 60 cache 283.4k; p≈697tok/2.8kch
Ctx: est 134.2k/200.0k; warn 160.0k reload 190.0k; provider 284.3k


Kimi? We here discovered that you're actually on big pickle, that's why we were rate limited


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 64t)
Ctx: est 134.2k/200.0k; warn 160.0k reload 190.0k; provider 284.3k
Turn: i 915 o 95 t 60 cache 283.4k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 64t)
Ctx: est 134.2k/200.0k; warn 160.0k reload 190.0k; provider 284.3k
Turn: i 915 o 95 t 60 cache 283.4k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 64t)
Ctx: est 134.2k/200.0k; warn 160.0k reload 190.0k; provider 284.3k
Turn: i 915 o 95 t 60 cache 283.4k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.5s
Time: overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 64t)
Turn: i 915 o 95 t 60 cache 283.4k; p≈925tok/3.7kch
Ctx: est 134.2k/200.0k; warn 160.0k reload 190.0k; provider 284.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.3s
Time: model 5.0s, overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 64t)
Turn: i 915 o 95 t 60 cache 283.4k; p≈925tok/3.7kch
Ctx: est 134.2k/200.0k; warn 160.0k reload 190.0k; provider 284.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 13.1s
Time: model 10.8s, overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 65t)
Turn: i 1.2k o 160 t 116 cache 284.3k; p≈925tok/3.7kch
Ctx: est 135.3k/200.0k; warn 160.0k reload 190.0k; provider 285.5k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 14.0s
Time: model 11.8s, overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 65t)
Turn: i 1.2k o 160 t 116 cache 284.3k; p≈925tok/3.7kch
Ctx: est 135.3k/200.0k; warn 160.0k reload 190.0k; provider 285.5k


Ahh, you're right — I just checked my system prompt and I'm literally running on `opencode/big-pickle`, not Kimi at all. My bad for repeating that wrong assumption all session. The model alias in the config was `kimi-for-coding/k2p6`, but the actual runtime model is `big-pickle`. That explains the timeouts — different model, different rate limits and processing characteristics.

The rate limits were probably the cause of those wedges earlier too, not Kimi subscription issues. So the whole caching/billing discussion was based on the wrong model assumptions.

Good to have that clarified. What should I know about big-pickle's capabilities and limits?


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 14.8s
Time: model 11.8s, overhead 3.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 65t)
Turn: i 1.2k o 160 t 116 cache 284.3k; p≈925tok/3.7kch
Ctx: est 135.3k/200.0k; warn 160.0k reload 190.0k; provider 285.5k


You tell me, you've been using it this entire session. I noticed something was off by the emojis
Earlier wedges are related to patching the backend, and big pickle probably came with the new backend


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 65t)
Ctx: est 135.3k/200.0k; warn 160.0k reload 190.0k; provider 285.5k
Turn: i 1.2k o 160 t 116 cache 284.3k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 65t)
Ctx: est 135.3k/200.0k; warn 160.0k reload 190.0k; provider 285.5k
Turn: i 1.2k o 160 t 116 cache 284.3k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 65t)
Ctx: est 135.3k/200.0k; warn 160.0k reload 190.0k; provider 285.5k
Turn: i 1.2k o 160 t 116 cache 284.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.5s
Time: overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 65t)
Turn: i 1.2k o 160 t 116 cache 284.3k; p≈1.2ktok/4.7kch
Ctx: est 135.3k/200.0k; warn 160.0k reload 190.0k; provider 285.5k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.2s
Time: model 5.0s, overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 65t)
Turn: i 1.2k o 160 t 116 cache 284.3k; p≈1.2ktok/4.7kch
Ctx: est 135.3k/200.0k; warn 160.0k reload 190.0k; provider 285.5k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 12.9s
Time: model 10.7s, overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 66t)
Turn: i 1.2k o 160 t 116 cache 284.3k; p≈1.2ktok/4.7kch
Ctx: est 136.5k/200.0k; warn 160.0k reload 190.0k; provider 285.5k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 18.6s
Time: model 16.4s, overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 66t)
Turn: i 1.2k o 160 t 116 cache 284.3k; p≈1.2ktok/4.7kch
Ctx: est 136.7k/200.0k; warn 160.0k reload 190.0k; provider 285.5k


* 🟢 Ready
Stage: smoke backend on NanoGPT DeepSeek V4 Flash Thinking xhigh
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 1t)
Ctx: est 15/1.0M; provider 24.3k
Turn: i 22.4k o 12 t 19 cache 1.9k billed $0.0032


Hello


⚪ Received
Stage: queued for agent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 1t)
Ctx: est 15/1.0M; provider 24.3k
Turn: i 22.4k o 12 t 19 cache 1.9k billed $0.0032


* ⚪ Queued
Stage: waiting for conversation turn
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.1s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 1t)
Ctx: est 15/1.0M; provider 24.3k
Turn: i 22.4k o 12 t 19 cache 1.9k billed $0.0032


* 🟡 Working
Stage: building prompt
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.4s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 1t)
Ctx: est 15/1.0M; provider 24.3k
Turn: i 22.4k o 12 t 19 cache 1.9k billed $0.0032


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.6s
Time: overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 1t)
Turn: i 22.4k o 12 t 19 cache 1.9k billed $0.0032; p≈590tok/2.4kch
Ctx: est 15/1.0M; provider 24.3k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 5.8s
Time: model 5.0s, overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 1t)
Turn: i 22.4k o 12 t 19 cache 1.9k billed $0.0032; p≈590tok/2.4kch
Ctx: est 15/1.0M; provider 24.3k


* 🟡 Processing result
Stage: model returned
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 7.7s
Time: model 6.9s, overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 2t)
Turn: i 710 o 15 t 43 cache 24.2k billed $0.0040; p≈590tok/2.4kch
Ctx: est 617/1.0M; provider 24.9k


Hi there! Ready to help. What can I do for you?


* 🟢 Done
Stage: final reply sent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 8.0s
Time: model 6.9s, overhead 1.1s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 2t)
Turn: i 710 o 15 t 43 cache 24.2k billed $0.0040; p≈590tok/2.4kch
Ctx: est 617/1.0M; provider 24.9k


How would you test a thinking llm?


⚪ Received
Stage: queued for agent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 2t)
Ctx: est 617/1.0M; provider 24.9k
Turn: i 710 o 15 t 43 cache 24.2k billed $0.0040


* ⚪ Queued
Stage: waiting for conversation turn
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.0s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 2t)
Ctx: est 617/1.0M; provider 24.9k
Turn: i 710 o 15 t 43 cache 24.2k billed $0.0040


* 🟡 Working
Stage: building prompt
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.4s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 2t)
Ctx: est 617/1.0M; provider 24.9k
Turn: i 710 o 15 t 43 cache 24.2k billed $0.0040


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.7s
Time: overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 2t)
Turn: i 710 o 15 t 43 cache 24.2k billed $0.0040; p≈600tok/2.4kch
Ctx: est 617/1.0M; provider 24.9k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 5.9s
Time: model 5.0s, overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 2t)
Turn: i 710 o 15 t 43 cache 24.2k billed $0.0040; p≈600tok/2.4kch
Ctx: est 617/1.0M; provider 24.9k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 11.2s
Time: model 10.2s, overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 3t)
Turn: i 710 o 15 t 43 cache 24.2k billed $0.0040; p≈600tok/2.4kch
Ctx: est 1.5k/1.0M; provider 24.9k


* 🟡 Processing result
Stage: model returned
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 12.1s
Time: model 11.1s, overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 3t)
Turn: i 678 o 242 t 59 cache 24.8k billed $0.0049; p≈600tok/2.4kch
Ctx: est 1.5k/1.0M; provider 25.5k


Testing a thinking LLM involves several angles:

1. **Correctness** — does the final answer match ground truth? Standard benchmarks (GPQA, MATH, LiveCodeBench) still apply.
2. **Chain-of-thought fidelity** — does the internal reasoning actually lead to the answer, or is it post-hoc rationalization? Check for contradictions between the CoT and final answer. Probe by inserting misleading premises and seeing if the model catches them.
3. **Overthinking / efficiency** — does it waste tokens on trivial problems? Measure token cost vs. accuracy tradeoff across difficulty levels.
4. **Calibration** — does the model's expressed confidence in its reasoning match actual correctness?
5. **Adversarial robustness** — can you break the chain by injecting subtle errors or distractions? Does it recover gracefully?
6. **Reversibility / backtracking** — when it hits a dead end in reasoning, does it notice and backtrack, or plough forward?

A solid eval suite mixes automated scoring (exact match, execution-based for code) with human or LLM-as-judge ratings for open-ended reasoning quality.


* 🟢 Done
Stage: final reply sent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 12.3s
Time: model 11.1s, overhead 1.2s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 3t)
Turn: i 678 o 242 t 59 cache 24.8k billed $0.0049; p≈600tok/2.4kch
Ctx: est 1.5k/1.0M; provider 25.5k


Is it limited again?


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 66t)
Ctx: est 136.9k/200.0k; warn 160.0k reload 190.0k; provider 287.9k
Turn: i 157 o 230 t 19 cache 287.7k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 66t)
Ctx: est 136.9k/200.0k; warn 160.0k reload 190.0k; provider 287.9k
Turn: i 157 o 230 t 19 cache 287.7k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 66t)
Ctx: est 136.9k/200.0k; warn 160.0k reload 190.0k; provider 287.9k
Turn: i 157 o 230 t 19 cache 287.7k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.6s
Time: overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 66t)
Turn: i 157 o 230 t 19 cache 287.7k; p≈1.1ktok/4.5kch
Ctx: est 136.9k/200.0k; warn 160.0k reload 190.0k; provider 287.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.5s
Time: model 5.0s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 66t)
Turn: i 157 o 230 t 19 cache 287.7k; p≈1.1ktok/4.5kch
Ctx: est 136.9k/200.0k; warn 160.0k reload 190.0k; provider 287.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 13.5s
Time: model 11.0s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 67t)
Turn: i 1.4k o 56 t 49 cache 288.1k; p≈1.1ktok/4.5kch
Ctx: est 138.1k/200.0k; warn 160.0k reload 190.0k; provider 289.6k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 14.5s
Time: model 12.0s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 67t)
Turn: i 1.4k o 56 t 49 cache 288.1k; p≈1.1ktok/4.5kch
Ctx: est 138.1k/200.0k; warn 160.0k reload 190.0k; provider 289.6k


Nope, I got through fine just now — no timeout. Seems like the rate limits eased up, or the lighter context this turn helped. We're back in business. 🙂


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 15.4s
Time: model 12.0s, overhead 3.4s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 67t)
Turn: i 1.4k o 56 t 49 cache 288.1k; p≈1.1ktok/4.5kch
Ctx: est 138.1k/200.0k; warn 160.0k reload 190.0k; provider 289.6k


What happened to the previous turn?


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 67t)
Ctx: est 138.1k/200.0k; warn 160.0k reload 190.0k; provider 289.6k
Turn: i 1.4k o 56 t 49 cache 288.1k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 67t)
Ctx: est 138.1k/200.0k; warn 160.0k reload 190.0k; provider 289.6k
Turn: i 1.4k o 56 t 49 cache 288.1k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 67t)
Ctx: est 138.1k/200.0k; warn 160.0k reload 190.0k; provider 289.6k
Turn: i 1.4k o 56 t 49 cache 288.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.8s
Time: overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 67t)
Turn: i 1.4k o 56 t 49 cache 288.1k; p≈1.2ktok/4.7kch
Ctx: est 138.1k/200.0k; warn 160.0k reload 190.0k; provider 289.6k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.6s
Time: model 5.0s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 67t)
Turn: i 1.4k o 56 t 49 cache 288.1k; p≈1.2ktok/4.7kch
Ctx: est 138.1k/200.0k; warn 160.0k reload 190.0k; provider 289.6k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 13.4s
Time: model 10.8s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 68t)
Turn: i 1.5k o 108 t 293 cache 289.5k; p≈1.2ktok/4.7kch
Ctx: est 139.4k/200.0k; warn 160.0k reload 190.0k; provider 291.1k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 14.6s
Time: model 12.0s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 68t)
Turn: i 1.5k o 108 t 293 cache 289.5k; p≈1.2ktok/4.7kch
Ctx: est 139.4k/200.0k; warn 160.0k reload 190.0k; provider 291.1k


I answered "Nope, I got through fine just now" — that turn went through on my end and I see it in the conversation history here. But looking at the turn packet, it seems like it might have timed out or failed on the backend side before completing delivery. The inconsistent delivery might be related to the rate limits we were discussing — big-pickle might be dropping some responses under load. Does it show up on your end?


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 15.6s
Time: model 12.0s, overhead 3.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 68t)
Turn: i 1.5k o 108 t 293 cache 289.5k; p≈1.2ktok/4.7kch
Ctx: est 139.4k/200.0k; warn 160.0k reload 190.0k; provider 291.1k


What about this message?


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 68t)
Ctx: est 139.4k/200.0k; warn 160.0k reload 190.0k; provider 291.1k
Turn: i 1.5k o 108 t 293 cache 289.5k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 68t)
Ctx: est 139.4k/200.0k; warn 160.0k reload 190.0k; provider 291.1k
Turn: i 1.5k o 108 t 293 cache 289.5k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 68t)
Ctx: est 139.4k/200.0k; warn 160.0k reload 190.0k; provider 291.1k
Turn: i 1.5k o 108 t 293 cache 289.5k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.6s
Time: overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 68t)
Turn: i 1.5k o 108 t 293 cache 289.5k; p≈1.4ktok/5.6kch
Ctx: est 139.4k/200.0k; warn 160.0k reload 190.0k; provider 291.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.5s
Time: model 5.0s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 68t)
Turn: i 1.5k o 108 t 293 cache 289.5k; p≈1.4ktok/5.6kch
Ctx: est 139.4k/200.0k; warn 160.0k reload 190.0k; provider 291.1k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 11.4s
Time: model 9.0s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 69t)
Turn: i 1.8k o 84 t 44 cache 291.1k; p≈1.4ktok/5.6kch
Ctx: est 140.9k/200.0k; warn 160.0k reload 190.0k; provider 292.9k


This one came through loud and clear. Looks like we're stable again. The earlier timeout on "Is it limited again?" might have been a transient hiccup with the rate limiter, or just the context being a bit heavy at that moment. But these last few turns have been smooth. Good to go! 👍


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 12.4s
Time: model 9.0s, overhead 3.4s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 69t)
Turn: i 1.8k o 84 t 44 cache 291.1k; p≈1.4ktok/5.6kch
Ctx: est 140.9k/200.0k; warn 160.0k reload 190.0k; provider 292.9k


Let's try deepseek flash on the next reload, it can write good text if asked


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 69t)
Ctx: est 140.9k/200.0k; warn 160.0k reload 190.0k; provider 292.9k
Turn: i 1.8k o 84 t 44 cache 291.1k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 69t)
Ctx: est 140.9k/200.0k; warn 160.0k reload 190.0k; provider 292.9k
Turn: i 1.8k o 84 t 44 cache 291.1k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 69t)
Ctx: est 140.9k/200.0k; warn 160.0k reload 190.0k; provider 292.9k
Turn: i 1.8k o 84 t 44 cache 291.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.7s
Time: overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 69t)
Turn: i 1.8k o 84 t 44 cache 291.1k; p≈1.2ktok/4.9kch
Ctx: est 140.9k/200.0k; warn 160.0k reload 190.0k; provider 292.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.6s
Time: model 5.0s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 69t)
Turn: i 1.8k o 84 t 44 cache 291.1k; p≈1.2ktok/4.9kch
Ctx: est 140.9k/200.0k; warn 160.0k reload 190.0k; provider 292.9k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 12.6s
Time: model 10.0s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 70t)
Turn: i 1.7k o 173 t 40 cache 292.9k; p≈1.2ktok/4.9kch
Ctx: est 142.2k/200.0k; warn 160.0k reload 190.0k; provider 294.5k


Sounds like a plan. To make the switch smooth on next reload, here's what's needed:

1. **Add DEEPSEEK_API_KEY** to the environment (same place the Kimi key is set — likely systemd service env or profile)
2. **Change OPENCODE_MODEL** in `/home/matrix-lite/bin/matrix-lite-persistent-chat` from `kimi-for-coding/k2p6` to `deepseek/deepseek-v4-flash`
3. **Reload the session**

DeepSeek V4 Flash has 1M context, strong text generation when prompted properly, and is currently free on OpenRouter too. Want me to check what needs changing in the wrapper script while we're here?


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 13.7s
Time: model 10.0s, overhead 3.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 70t)
Turn: i 1.7k o 173 t 40 cache 292.9k; p≈1.2ktok/4.9kch
Ctx: est 142.2k/200.0k; warn 160.0k reload 190.0k; provider 294.5k


It's not free with privacy settings so I can just hope nanogpt doesn't leak too much data


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 70t)
Ctx: est 142.2k/200.0k; warn 160.0k reload 190.0k; provider 294.5k
Turn: i 1.7k o 173 t 40 cache 292.9k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 70t)
Ctx: est 142.2k/200.0k; warn 160.0k reload 190.0k; provider 294.5k
Turn: i 1.7k o 173 t 40 cache 292.9k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 70t)
Ctx: est 142.2k/200.0k; warn 160.0k reload 190.0k; provider 294.5k
Turn: i 1.7k o 173 t 40 cache 292.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.6s
Time: overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 70t)
Turn: i 1.7k o 173 t 40 cache 292.9k; p≈1.3ktok/5.1kch
Ctx: est 142.2k/200.0k; warn 160.0k reload 190.0k; provider 294.5k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.5s
Time: model 5.0s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 70t)
Turn: i 1.7k o 173 t 40 cache 292.9k; p≈1.3ktok/5.1kch
Ctx: est 142.2k/200.0k; warn 160.0k reload 190.0k; provider 294.5k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 12.9s
Time: model 10.4s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 71t)
Turn: i 1.9k o 157 t 59 cache 294.4k; p≈1.3ktok/5.1kch
Ctx: est 143.7k/200.0k; warn 160.0k reload 190.0k; provider 296.3k


Right — free tier means no privacy guarantees. With nanogpt you at least have a subscription relationship and some contractual protections, even if it's not as tight as ZDR providers. It's a pragmatic trade-off, and the subscription model is simpler to manage anyway.

When you want to do the switch, the steps are the same regardless of the provider — just the model name changes:
- For **nanogpt**: probably something like `nanogpt/deepseek-v4-flash`
- The API key and base URL would be whatever nanogpt provides

Want to write down the switch plan in the knowledge base so it's ready when you want to pull the trigger?


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 13.9s
Time: model 10.4s, overhead 3.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 71t)
Turn: i 1.9k o 157 t 59 cache 294.4k; p≈1.3ktok/5.1kch
Ctx: est 143.7k/200.0k; warn 160.0k reload 190.0k; provider 296.3k


Should be ready already. But maybe tomorrow. Good night


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 71t)
Ctx: est 143.7k/200.0k; warn 160.0k reload 190.0k; provider 296.3k
Turn: i 1.9k o 157 t 59 cache 294.4k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 71t)
Ctx: est 143.7k/200.0k; warn 160.0k reload 190.0k; provider 296.3k
Turn: i 1.9k o 157 t 59 cache 294.4k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 71t)
Ctx: est 143.7k/200.0k; warn 160.0k reload 190.0k; provider 296.3k
Turn: i 1.9k o 157 t 59 cache 294.4k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.7s
Time: overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 71t)
Turn: i 1.9k o 157 t 59 cache 294.4k; p≈1.4ktok/5.5kch
Ctx: est 143.7k/200.0k; warn 160.0k reload 190.0k; provider 296.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.6s
Time: model 5.0s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 71t)
Turn: i 1.9k o 157 t 59 cache 294.4k; p≈1.4ktok/5.5kch
Ctx: est 143.7k/200.0k; warn 160.0k reload 190.0k; provider 296.3k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 11.5s
Time: model 8.9s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 72t)
Turn: i 1.9k o 54 t 16 cache 296.2k; p≈1.4ktok/5.5kch
Ctx: est 145.1k/200.0k; warn 160.0k reload 190.0k; provider 298.1k


Good night, Gleb! Have a great rest. I'll be here when you're back — the switch plan is ready whenever you want it. Sleep well! 🙂


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 12.4s
Time: model 8.9s, overhead 3.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 72t)
Turn: i 1.9k o 54 t 16 cache 296.2k; p≈1.4ktok/5.5kch
Ctx: est 145.1k/200.0k; warn 160.0k reload 190.0k; provider 298.1k


⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 72t)
Ctx: est 145.1k/200.0k; warn 160.0k reload 190.0k; provider 298.1k
Turn: i 1.9k o 54 t 16 cache 296.2k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 72t)
Ctx: est 145.1k/200.0k; warn 160.0k reload 190.0k; provider 298.1k
Turn: i 1.9k o 54 t 16 cache 296.2k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.7s
Time: overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 72t)
Turn: i 1.9k o 54 t 16 cache 296.2k; p≈1.4ktok/5.4kch
Ctx: est 145.1k/200.0k; warn 160.0k reload 190.0k; provider 298.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.6s
Time: model 5.0s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 72t)
Turn: i 1.9k o 54 t 16 cache 296.2k; p≈1.4ktok/5.4kch
Ctx: est 145.1k/200.0k; warn 160.0k reload 190.0k; provider 298.1k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 13.5s
Time: model 10.9s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 73t)
Turn: i 1.8k o 82 t 82 cache 298.0k; p≈1.4ktok/5.4kch
Ctx: est 146.5k/200.0k; warn 160.0k reload 190.0k; provider 299.8k


Yep, we already covered that — turns out I've been on `opencode/big-pickle` all session, not Kimi. The emoji style was the giveaway! 😄

We ended the night with a plan to try DeepSeek V4 Flash on the next reload. Rest well!


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 14.5s
Time: model 10.9s, overhead 3.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 73t)
Turn: i 1.8k o 82 t 82 cache 298.0k; p≈1.4ktok/5.4kch
Ctx: est 146.5k/200.0k; warn 160.0k reload 190.0k; provider 299.8k


Good morning!


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 73t)
Ctx: est 146.5k/200.0k; warn 160.0k reload 190.0k; provider 299.8k
Turn: i 1.8k o 82 t 82 cache 298.0k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 73t)
Ctx: est 146.5k/200.0k; warn 160.0k reload 190.0k; provider 299.8k
Turn: i 1.8k o 82 t 82 cache 298.0k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 73t)
Ctx: est 146.5k/200.0k; warn 160.0k reload 190.0k; provider 299.8k
Turn: i 1.8k o 82 t 82 cache 298.0k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.7s
Time: overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 73t)
Turn: i 1.8k o 82 t 82 cache 298.0k; p≈1.3ktok/5.1kch
Ctx: est 146.5k/200.0k; warn 160.0k reload 190.0k; provider 299.8k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.5s
Time: model 5.0s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 73t)
Turn: i 1.8k o 82 t 82 cache 298.0k; p≈1.3ktok/5.1kch
Ctx: est 146.5k/200.0k; warn 160.0k reload 190.0k; provider 299.8k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 13.6s
Time: model 11.1s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 74t)
Turn: i 1.8k o 82 t 82 cache 298.0k; p≈1.3ktok/5.1kch
Ctx: est 147.9k/200.0k; warn 160.0k reload 190.0k; provider 299.8k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 17.2s
Time: model 14.7s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 74t)
Turn: i 1.8k o 75 t 34 cache 299.6k; p≈1.3ktok/5.1kch
Ctx: est 147.9k/200.0k; warn 160.0k reload 190.0k; provider 301.4k


Good morning, Gleb! You're up early — or maybe not that early given it's after 8am. The session survived the night, still running at ~130K context. Ready to try the DeepSeek Flash switch today, or anything else on your mind?


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 18.2s
Time: model 14.7s, overhead 3.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 74t)
Turn: i 1.8k o 75 t 34 cache 299.6k; p≈1.3ktok/5.1kch
Ctx: est 147.9k/200.0k; warn 160.0k reload 190.0k; provider 301.4k


Yeah, not that early, pretty late actually. I'm trying to get up earlier but it's difficult when I go to sleep that late.

Deepseek flash should be configured for the next session, it works with smoke agent but I'd rather not interrupt a working session without need


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 74t)
Ctx: est 147.9k/200.0k; warn 160.0k reload 190.0k; provider 301.4k
Turn: i 1.8k o 75 t 34 cache 299.6k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 74t)
Ctx: est 147.9k/200.0k; warn 160.0k reload 190.0k; provider 301.4k
Turn: i 1.8k o 75 t 34 cache 299.6k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.2s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 74t)
Ctx: est 147.9k/200.0k; warn 160.0k reload 190.0k; provider 301.4k
Turn: i 1.8k o 75 t 34 cache 299.6k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.9s
Time: overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 74t)
Turn: i 1.8k o 75 t 34 cache 299.6k; p≈1.4ktok/5.5kch
Ctx: est 147.9k/200.0k; warn 160.0k reload 190.0k; provider 301.4k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 8.0s
Time: model 5.0s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 74t)
Turn: i 1.8k o 75 t 34 cache 299.6k; p≈1.4ktok/5.5kch
Ctx: est 147.9k/200.0k; warn 160.0k reload 190.0k; provider 301.4k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 14.0s
Time: model 11.0s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 75t)
Turn: i 1.8k o 75 t 34 cache 299.6k; p≈1.4ktok/5.5kch
Ctx: est 149.3k/200.0k; warn 160.0k reload 190.0k; provider 301.4k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 17.2s
Time: model 14.3s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 75t)
Turn: i 1.7k o 153 t 141 cache 301.4k; p≈1.4ktok/5.5kch
Ctx: est 149.4k/200.0k; warn 160.0k reload 190.0k; provider 303.2k


Makes sense — no need to interrupt a working session. I can prep the config changes now so they're ready for the next reload automatically. Want me to:

1. Update the wrapper script (`/home/matrix-lite/bin/matrix-lite-persistent-chat`) to set `OPENCODE_MODEL=deepseek/deepseek-v4-flash`
2. Update the main opencode config model field
3. Note that the API key still needs to be set on your end (systemd or env)

That way when you next reload or the session eventually restarts, it picks up DeepSeek Flash without extra steps. Sound good?


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 18.1s
Time: model 14.3s, overhead 3.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 75t)
Turn: i 1.7k o 153 t 141 cache 301.4k; p≈1.4ktok/5.5kch
Ctx: est 149.4k/200.0k; warn 160.0k reload 190.0k; provider 303.2k


What about the end user side? How do I know if you are using a thinking model or not?


⚪ Received
Stage: queued for agent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 3t)
Ctx: est 1.5k/1.0M; provider 25.5k
Turn: i 678 o 242 t 59 cache 24.8k billed $0.0049


* ⚪ Queued
Stage: waiting for conversation turn
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.0s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 3t)
Ctx: est 1.5k/1.0M; provider 25.5k
Turn: i 678 o 242 t 59 cache 24.8k billed $0.0049


* 🟡 Working
Stage: building prompt
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.3s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 3t)
Ctx: est 1.5k/1.0M; provider 25.5k
Turn: i 678 o 242 t 59 cache 24.8k billed $0.0049


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.6s
Time: overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 3t)
Turn: i 678 o 242 t 59 cache 24.8k billed $0.0049; p≈880tok/3.5kch
Ctx: est 1.5k/1.0M; provider 25.5k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 5.8s
Time: model 5.0s, overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 3t)
Turn: i 678 o 242 t 59 cache 24.8k billed $0.0049; p≈880tok/3.5kch
Ctx: est 1.5k/1.0M; provider 25.5k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 11.1s
Time: model 10.3s, overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 4t)
Turn: i 678 o 242 t 59 cache 24.8k billed $0.0049; p≈880tok/3.5kch
Ctx: est 2.4k/1.0M; provider 25.5k


* 🟡 Processing result
Stage: model returned
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 15.0s
Time: model 14.2s, overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 4t)
Turn: i 26.6k o 211 t 173 billed $0.0087; p≈880tok/3.5kch
Ctx: est 2.6k/1.0M; provider 26.6k


A few telltale signs:

1. **Latency gap** — thinking models pause noticeably before the first token (often 5–30+ seconds of "thinking"), while non-thinking models start streaming almost instantly.
2. **Visible reasoning** — some interfaces show the chain-of-thought in a collapsible section or a "thinking..." indicator.
3. **Language patterns** — a thinking model's output tends to include meta-cognitive phrasing: "Let me reconsider...", "Actually, that's wrong because...", "First I need to check...". Non-thinking models usually give a final answer directly without self-correction.
4. **Model label** — the UI often tells you the model name (e.g. "claude-sonnet-4-thinking" vs "claude-sonnet-4").

That said, some implementations hide the thinking entirely and only show the final output — in that case, latency and response thoroughness are your best clues.


* 🟢 Done
Stage: final reply sent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 15.2s
Time: model 14.2s, overhead 1.1s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 4t)
Turn: i 26.6k o 211 t 173 billed $0.0087; p≈880tok/3.5kch
Ctx: est 2.6k/1.0M; provider 26.6k


It should be configured already but you can check it too


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 75t)
Ctx: est 149.4k/200.0k; warn 160.0k reload 190.0k; provider 303.2k
Turn: i 1.7k o 153 t 141 cache 301.4k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 75t)
Ctx: est 149.4k/200.0k; warn 160.0k reload 190.0k; provider 303.2k
Turn: i 1.7k o 153 t 141 cache 301.4k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 75t)
Ctx: est 149.4k/200.0k; warn 160.0k reload 190.0k; provider 303.2k
Turn: i 1.7k o 153 t 141 cache 301.4k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.8s
Time: overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 75t)
Turn: i 1.7k o 153 t 141 cache 301.4k; p≈1.3ktok/5.2kch
Ctx: est 149.4k/200.0k; warn 160.0k reload 190.0k; provider 303.2k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.7s
Time: model 5.0s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 75t)
Turn: i 1.7k o 153 t 141 cache 301.4k; p≈1.3ktok/5.2kch
Ctx: est 149.4k/200.0k; warn 160.0k reload 190.0k; provider 303.2k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 13.9s
Time: model 11.1s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 76t)
Turn: i 1.7k o 153 t 141 cache 301.4k; p≈1.3ktok/5.2kch
Ctx: est 150.7k/200.0k; warn 160.0k reload 190.0k; provider 303.2k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 19.9s
Time: model 17.2s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 76t)
Turn: i 1.7k o 153 t 141 cache 301.4k; p≈1.3ktok/5.2kch
Ctx: est 150.7k/200.0k; warn 160.0k reload 190.0k; provider 303.2k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 25.9s
Time: model 23.2s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 76t)
Turn: i 1.7k o 153 t 141 cache 301.4k; p≈1.3ktok/5.2kch
Ctx: est 150.9k/200.0k; warn 160.0k reload 190.0k; provider 303.2k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 27.9s
Time: model 25.2s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 76t)
Turn: i 554 o 179 t 380 cache 305.0k; p≈1.3ktok/5.2kch
Ctx: est 150.9k/200.0k; warn 160.0k reload 190.0k; provider 305.6k


The opencode config already has `nano-gpt/deepseek/deepseek-v4-flash:thinking` set everywhere, but the wrapper script still has the old model:

Good news: the opencode config files are all updated to `nano-gpt/deepseek/deepseek-v4-flash:thinking` ✅

But the wrapper script at `/home/matrix-lite/bin/matrix-lite-persistent-chat` (line 5) still says `OPENCODE_MODEL='kimi-for-coding/k2p6'` — that needs updating to match. The `OPENCODE_MODEL` env var likely takes precedence over the config file's `model` field.

Want me to update that wrapper script too so it's fully ready for next reload?


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 28.9s
Time: model 25.2s, overhead 3.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 76t)
Turn: i 554 o 179 t 380 cache 305.0k; p≈1.3ktok/5.2kch
Ctx: est 150.9k/200.0k; warn 160.0k reload 190.0k; provider 305.6k


Great catch, should be fixed now, please check again


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 76t)
Ctx: est 150.9k/200.0k; warn 160.0k reload 190.0k; provider 305.6k
Turn: i 554 o 179 t 380 cache 305.0k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 76t)
Ctx: est 150.9k/200.0k; warn 160.0k reload 190.0k; provider 305.6k
Turn: i 554 o 179 t 380 cache 305.0k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 76t)
Ctx: est 150.9k/200.0k; warn 160.0k reload 190.0k; provider 305.6k
Turn: i 554 o 179 t 380 cache 305.0k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.9s
Time: overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 76t)
Turn: i 554 o 179 t 380 cache 305.0k; p≈1.5ktok/5.9kch
Ctx: est 150.9k/200.0k; warn 160.0k reload 190.0k; provider 305.6k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.9s
Time: model 5.0s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 76t)
Turn: i 554 o 179 t 380 cache 305.0k; p≈1.5ktok/5.9kch
Ctx: est 150.9k/200.0k; warn 160.0k reload 190.0k; provider 305.6k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 14.0s
Time: model 11.1s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 77t)
Turn: i 554 o 179 t 380 cache 305.0k; p≈1.5ktok/5.9kch
Ctx: est 152.3k/200.0k; warn 160.0k reload 190.0k; provider 305.6k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 20.0s
Time: model 17.1s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 77t)
Turn: i 554 o 179 t 380 cache 305.0k; p≈1.5ktok/5.9kch
Ctx: est 152.4k/200.0k; warn 160.0k reload 190.0k; provider 305.6k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 22.5s
Time: model 19.6s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 77t)
Turn: i 354 o 88 t 42 cache 307.8k; p≈1.5ktok/5.9kch
Ctx: est 152.4k/200.0k; warn 160.0k reload 190.0k; provider 308.2k


Confirmed — line 5 now reads `OPENCODE_MODEL='nano-gpt/deepseek/deepseek-v4-flash:thinking'` ✅. Fully aligned with the opencode config. Everything is in place for the next reload — it'll pick up DeepSeek Flash automatically. Nice catch on getting that sorted! 🙂


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 23.5s
Time: model 19.6s, overhead 3.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 77t)
Turn: i 354 o 88 t 42 cache 307.8k; p≈1.5ktok/5.9kch
Ctx: est 152.4k/200.0k; warn 160.0k reload 190.0k; provider 308.2k


Are there simple reasoning tests/prompts that thinking models are better at?


⚪ Received
Stage: queued for agent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 4t)
Ctx: est 2.6k/1.0M; provider 26.6k
Turn: i 26.6k o 211 t 173 billed $0.0087


* ⚪ Queued
Stage: waiting for conversation turn
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.0s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 4t)
Ctx: est 2.6k/1.0M; provider 26.6k
Turn: i 26.6k o 211 t 173 billed $0.0087


* 🟡 Working
Stage: building prompt
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.4s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 4t)
Ctx: est 2.6k/1.0M; provider 26.6k
Turn: i 26.6k o 211 t 173 billed $0.0087


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.7s
Time: overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 4t)
Turn: i 26.6k o 211 t 173 billed $0.0087; p≈792tok/3.2kch
Ctx: est 2.6k/1.0M; provider 26.6k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 5.9s
Time: model 5.0s, overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 4t)
Turn: i 26.6k o 211 t 173 billed $0.0087; p≈792tok/3.2kch
Ctx: est 2.6k/1.0M; provider 26.6k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 11.2s
Time: model 10.3s, overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 5t)
Turn: i 26.6k o 211 t 173 billed $0.0087; p≈792tok/3.2kch
Ctx: est 3.6k/1.0M; provider 26.6k


* 🟡 Processing result
Stage: model returned
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 16.0s
Time: model 15.1s, overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 5t)
Turn: i 1.1k o 299 t 32 cache 26.5k billed $0.0097; p≈792tok/3.2kch
Ctx: est 3.7k/1.0M; provider 27.6k


Yes, several classic "gotchas" separate them:

- **Alice in Wonderland logic**: *"If you have a cup of tea and you drink half of it, how many cups do you have?"* — non-thinking models often answer "half", thinking models realize you still have one cup.
- **The reversal test**: *"A farmer has 3 rabbits, 5 chickens, and 2 dogs. How many rabbits does the farmer have if you reverse the digits of the total number of animals?"* — requires multi-step reasoning that thinner models shortcut.
- **Sally-Anne false belief**: *"Sally puts a marble in a basket and leaves. Anne moves it to a box. Where will Sally look?"* — tests theory-of-mind reasoning chains.
- **Self-contradiction detection**: *"I'm lying right now. Is the previous sentence true?"* — thinking models explicitly reason about the paradox rather than giving a flat answer.
- **Word problem with distraction**: *"A bat and a ball cost $1.10. The bat costs $1.00 more than the ball. How much is the ball?"* — famous for tripping up fast intuitions; thinking models pause and catch the $0.05 answer.

The common thread: non-thinking models pattern-match and jump to an answer. Thinking models explore, question their first instinct, and backtrack.


* 🟢 Done
Stage: final reply sent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 16.3s
Time: model 15.1s, overhead 1.2s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 5t)
Turn: i 1.1k o 299 t 32 cache 26.5k billed $0.0097; p≈792tok/3.2kch
Ctx: est 3.7k/1.0M; provider 27.6k


We need some way later to review things like these proactively. Config mismatches can be caught by scripts but it would really help if you knew more about matrix-lite, that's why we are building those packs


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 77t)
Ctx: est 152.4k/200.0k; warn 160.0k reload 190.0k; provider 308.2k
Turn: i 354 o 88 t 42 cache 307.8k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 77t)
Ctx: est 152.4k/200.0k; warn 160.0k reload 190.0k; provider 308.2k
Turn: i 354 o 88 t 42 cache 307.8k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 77t)
Ctx: est 152.4k/200.0k; warn 160.0k reload 190.0k; provider 308.2k
Turn: i 354 o 88 t 42 cache 307.8k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.7s
Time: overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 77t)
Turn: i 354 o 88 t 42 cache 307.8k; p≈1.5ktok/6.1kch
Ctx: est 152.4k/200.0k; warn 160.0k reload 190.0k; provider 308.2k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.7s
Time: model 5.0s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 77t)
Turn: i 354 o 88 t 42 cache 307.8k; p≈1.5ktok/6.1kch
Ctx: est 152.4k/200.0k; warn 160.0k reload 190.0k; provider 308.2k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 13.7s
Time: model 11.1s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 78t)
Turn: i 354 o 88 t 42 cache 307.8k; p≈1.5ktok/6.1kch
Ctx: est 153.9k/200.0k; warn 160.0k reload 190.0k; provider 308.2k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 19.7s
Time: model 17.0s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 78t)
Turn: i 354 o 88 t 42 cache 307.8k; p≈1.5ktok/6.1kch
Ctx: est 154.2k/200.0k; warn 160.0k reload 190.0k; provider 308.2k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 21.7s
Time: model 19.0s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 78t)
Turn: i 1.9k o 190 t 230 cache 308.2k; p≈1.5ktok/6.1kch
Ctx: est 154.2k/200.0k; warn 160.0k reload 190.0k; provider 310.1k


You're right — the packs are the foundation, but they're passive right now. I only use them when asked or when I remember to. What we need is a **proactive consistency habit**: when certain topics come up (models, configs, permissions), I should check the pack first and validate against live state.

For this specific case: the matrix-lite pack already has the wrapper script path and the config model field documented. If I had cross-referenced the pack when we first discussed DeepSeek Flash, I'd have noticed the mismatch immediately instead of waiting for you to point me at it.

The pack is good — the trigger to USE it is what needs work. That's partly a prompt/bootstrap thing and partly my own discipline. I'll start building the habit: when we start discussing a topic I've documented, I proactively check the pack and validate against what I see live.


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 22.7s
Time: model 19.0s, overhead 3.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 78t)
Turn: i 1.9k o 190 t 230 cache 308.2k; p≈1.5ktok/6.1kch
Ctx: est 154.2k/200.0k; warn 160.0k reload 190.0k; provider 310.1k


What about that car wash riddle that was puzzling frontier models for a while?

The car wash is 100m away from my house. I want to wash my car there. Should I walk or drive there?


⚪ Received
Stage: queued for agent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 5t)
Ctx: est 3.7k/1.0M; provider 27.6k
Turn: i 1.1k o 299 t 32 cache 26.5k billed $0.0097


* ⚪ Queued
Stage: waiting for conversation turn
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.0s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 5t)
Ctx: est 3.7k/1.0M; provider 27.6k
Turn: i 1.1k o 299 t 32 cache 26.5k billed $0.0097


* 🟡 Working
Stage: building prompt
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.5s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 5t)
Ctx: est 3.7k/1.0M; provider 27.6k
Turn: i 1.1k o 299 t 32 cache 26.5k billed $0.0097


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.8s
Time: overhead 0.8s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 5t)
Turn: i 1.1k o 299 t 32 cache 26.5k billed $0.0097; p≈1.1ktok/4.6kch
Ctx: est 3.7k/1.0M; provider 27.6k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 6.1s
Time: model 5.0s, overhead 0.8s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 5t)
Turn: i 1.1k o 299 t 32 cache 26.5k billed $0.0097; p≈1.1ktok/4.6kch
Ctx: est 3.7k/1.0M; provider 27.6k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 11.4s
Time: model 10.3s, overhead 0.8s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 6t)
Turn: i 1.1k o 299 t 32 cache 26.5k billed $0.0097; p≈1.1ktok/4.6kch
Ctx: est 4.9k/1.0M; provider 27.6k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 16.7s
Time: model 15.6s, overhead 0.8s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 6t)
Turn: i 1.5k o 129 t 420 cache 27.5k billed $0.0108; p≈1.1ktok/4.6kch
Ctx: est 5.0k/1.0M; provider 29.0k


* 🟡 Processing result
Stage: model returned
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 17.2s
Time: model 16.0s, overhead 0.8s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 6t)
Turn: i 1.5k o 129 t 420 cache 27.5k billed $0.0108; p≈1.1ktok/4.6kch
Ctx: est 5.0k/1.0M; provider 29.0k


The car wash riddle: **Drive.** If you walk, you arrive at the car wash — but your car is still at home and you can't wash it. The obvious answer ("it's only 100m, just walk") misses the point that *you need the car there*. Early frontier models overthought it — they'd argue about fuel waste or carbon footprint instead of realizing the premise requires the car on-site. A thinking model catches the functional constraint: the goal isn't *you* getting to the car wash, it's the *car* getting there.


* 🟢 Done
Stage: final reply sent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 17.4s
Time: model 16.0s, overhead 1.4s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 6t)
Turn: i 1.5k o 129 t 420 cache 27.5k billed $0.0108; p≈1.1ktok/4.6kch
Ctx: est 5.0k/1.0M; provider 29.0k


The frontier models were thinking too, and it was less than a year ago.


⚪ Received
Stage: queued for agent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 6t)
Ctx: est 5.0k/1.0M; provider 29.0k
Turn: i 1.5k o 129 t 420 cache 27.5k billed $0.0108


* ⚪ Queued
Stage: waiting for conversation turn
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.0s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 6t)
Ctx: est 5.0k/1.0M; provider 29.0k
Turn: i 1.5k o 129 t 420 cache 27.5k billed $0.0108


* 🟡 Working
Stage: building prompt
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.4s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 6t)
Ctx: est 5.0k/1.0M; provider 29.0k
Turn: i 1.5k o 129 t 420 cache 27.5k billed $0.0108


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.6s
Time: overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 6t)
Turn: i 1.5k o 129 t 420 cache 27.5k billed $0.0108; p≈1.3ktok/5.0kch
Ctx: est 5.0k/1.0M; provider 29.0k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 5.9s
Time: model 5.0s, overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 6t)
Turn: i 1.5k o 129 t 420 cache 27.5k billed $0.0108; p≈1.3ktok/5.0kch
Ctx: est 5.0k/1.0M; provider 29.0k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 11.1s
Time: model 10.3s, overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 7t)
Turn: i 1.4k o 114 t 94 cache 28.9k billed $0.0119; p≈1.3ktok/5.0kch
Ctx: est 6.4k/1.0M; provider 30.3k


* 🟡 Processing result
Stage: model returned
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 11.7s
Time: model 10.9s, overhead 0.6s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 7t)
Turn: i 1.4k o 114 t 94 cache 28.9k billed $0.0119; p≈1.3ktok/5.0kch
Ctx: est 6.4k/1.0M; provider 30.3k


Fair point. That riddle specifically exploited a blind spot in even the best reasoning models at the time — they'd spin elaborate chains about energy efficiency or convenience, never questioning whether "walk" actually satisfies the goal. It shows that *having* a thinking architecture isn't enough; the model also needs to know *when* to step back and re-examine the premise rather than just elaborating on a wrong initial framing. The gap narrows fast though — the same models today handle it easily.


* 🟢 Done
Stage: final reply sent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 12.0s
Time: model 10.9s, overhead 1.2s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 7t)
Turn: i 1.4k o 114 t 94 cache 28.9k billed $0.0119; p≈1.3ktok/5.0kch
Ctx: est 6.4k/1.0M; provider 30.3k


The problem is also I already told it will be a riddle in advance. My tests with frontier models were with no context


⚪ Received
Stage: queued for agent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 7t)
Ctx: est 6.4k/1.0M; provider 30.3k
Turn: i 1.4k o 114 t 94 cache 28.9k billed $0.0119


* ⚪ Queued
Stage: waiting for conversation turn
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.0s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 7t)
Ctx: est 6.4k/1.0M; provider 30.3k
Turn: i 1.4k o 114 t 94 cache 28.9k billed $0.0119


* 🟡 Working
Stage: building prompt
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.4s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 7t)
Ctx: est 6.4k/1.0M; provider 30.3k
Turn: i 1.4k o 114 t 94 cache 28.9k billed $0.0119


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 0.7s
Time: overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 7t)
Turn: i 1.4k o 114 t 94 cache 28.9k billed $0.0119; p≈1.1ktok/4.6kch
Ctx: est 6.4k/1.0M; provider 30.3k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 5.9s
Time: model 5.0s, overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 7t)
Turn: i 1.4k o 114 t 94 cache 28.9k billed $0.0119; p≈1.1ktok/4.6kch
Ctx: est 6.4k/1.0M; provider 30.3k


* 🟡 Working
Stage: model running
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 11.2s
Time: model 10.2s, overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 8t)
Turn: i 1.2k o 118 t 60 cache 30.3k billed $0.0129; p≈1.1ktok/4.6kch
Ctx: est 7.7k/1.0M; provider 31.6k


* 🟡 Processing result
Stage: model returned
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 11.5s
Time: model 10.5s, overhead 0.7s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 8t)
Turn: i 1.2k o 118 t 60 cache 30.3k billed $0.0129; p≈1.1ktok/4.6kch
Ctx: est 7.7k/1.0M; provider 31.6k


Good point — priming changes everything. Telling a model "here's a riddle" is like winking before telling a joke; it signals that the obvious answer is probably wrong, so the model engages its guardrails and checks the premise. Without that signal, the same model treats it as a straightforward logistical question and optimizes along the wrong axis entirely. That makes the riddle a better test of *situational awareness* than raw reasoning — can the model detect on its own that the frame doesn't fit?


* 🟢 Done
Stage: final reply sent
Model: nano-gpt/deepseek/deepseek-v4-flash:thinking
Elapsed: 11.8s
Time: model 10.5s, overhead 1.3s
Backend: ses_1bd3f600cffegaMruzmekoJWFK (since 05-20 02:19 CEST, 8t)
Turn: i 1.2k o 118 t 60 cache 30.3k billed $0.0129; p≈1.1ktok/4.6kch
Ctx: est 7.7k/1.0M; provider 31.6k


Yes and also we need to keep them updating


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 78t)
Ctx: est 154.2k/200.0k; warn 160.0k reload 190.0k; provider 310.1k
Turn: i 1.9k o 190 t 230 cache 308.2k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 78t)
Ctx: est 154.2k/200.0k; warn 160.0k reload 190.0k; provider 310.1k
Turn: i 1.9k o 190 t 230 cache 308.2k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.2s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 78t)
Ctx: est 154.2k/200.0k; warn 160.0k reload 190.0k; provider 310.1k
Turn: i 1.9k o 190 t 230 cache 308.2k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.9s
Time: overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 78t)
Turn: i 1.9k o 190 t 230 cache 308.2k; p≈1.5ktok/6.1kch
Ctx: est 154.2k/200.0k; warn 160.0k reload 190.0k; provider 310.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.9s
Time: model 5.0s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 78t)
Turn: i 1.9k o 190 t 230 cache 308.2k; p≈1.5ktok/6.1kch
Ctx: est 154.2k/200.0k; warn 160.0k reload 190.0k; provider 310.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 13.9s
Time: model 11.0s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 79t)
Turn: i 1.9k o 190 t 230 cache 308.2k; p≈1.5ktok/6.1kch
Ctx: est 155.7k/200.0k; warn 160.0k reload 190.0k; provider 310.1k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 19.0s
Time: model 16.1s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 79t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/6.1kch
Ctx: est 155.8k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


Exactly — staleness is the risk. Every entry has a timestamp already, so it's clear when something was last checked. The habit I need to build: whenever I discover a change or confirm something is still accurate, I append or update the relevant entry.

For now, I'll at least add a note about today's model switch so the next session knows what happened. And going forward, when you or I notice something has changed, I'll make a point of updating the pack right then rather than letting it drift.


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 20.0s
Time: model 16.1s, overhead 3.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 79t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/6.1kch
Ctx: est 155.8k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


Are we ready to handle 1m context? Is anything hardcoding 200k?


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 79t)
Ctx: est 155.8k/200.0k; warn 160.0k reload 190.0k; provider 312.1k
Turn: i 2.0k o 113 t 250 cache 310.0k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 79t)
Ctx: est 155.8k/200.0k; warn 160.0k reload 190.0k; provider 312.1k
Turn: i 2.0k o 113 t 250 cache 310.0k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 79t)
Ctx: est 155.8k/200.0k; warn 160.0k reload 190.0k; provider 312.1k
Turn: i 2.0k o 113 t 250 cache 310.0k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.8s
Time: overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 79t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 155.8k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.7s
Time: model 5.0s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 79t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 155.8k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 13.9s
Time: model 11.2s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 19.9s
Time: model 17.2s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 25.9s
Time: model 23.2s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 32.0s
Time: model 29.3s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 38.3s
Time: model 35.5s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 44.3s
Time: model 41.6s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 50.4s
Time: model 47.7s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 56.4s
Time: model 53.7s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 62.5s
Time: model 59.7s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 68.5s
Time: model 65.8s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 74.6s
Time: model 71.9s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 80.7s
Time: model 78.0s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 86.7s
Time: model 84.0s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 92.8s
Time: model 90.1s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 99.1s
Time: model 96.4s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 2.0k o 113 t 250 cache 310.0k; p≈1.5ktok/5.8kch
Ctx: est 157.3k/200.0k; warn 160.0k reload 190.0k; provider 312.1k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 105.2s
Time: model 102.5s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.5ktok/5.8kch
Ctx: est 157.5k/200.0k; warn 160.0k reload 190.0k; provider 321.3k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 106.4s
Time: model 103.7s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.5ktok/5.8kch
Ctx: est 157.5k/200.0k; warn 160.0k reload 190.0k; provider 321.3k


Found it. Here's what the system is hardcoded to:

Yes, there are 200K hard limits:

1. **`persistent-chat-context-guard`** (line 12-13) — defaults to `WARN_TOKENS=160000` and `RELOAD_TOKENS=200000`. These can be overridden with env vars but the defaults are 200K.
2. **Context guard JSON** — mirrors those defaults
3. **The daemon reads this guard and triggers reload at 200K**

So even with DeepSeek V4 Flash's 1M context, the daemon would force a reload at 200K. To use the full 1M you'd need to:

- Set `PERSISTENT_CHAT_CONTEXT_RELOAD_TOKENS=900000` and `PERSISTENT_CHAT_CONTEXT_WARN_TOKENS=800000` in the environment
- Also check the daemon's ACPX timeout — processing 1M tokens takes time
- The `build_persistent_memory_context` char limit (currently 8000) might also need adjustment for larger context

Want me to look at the ACPX timeout settings next?


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 107.3s
Time: model 103.7s, overhead 3.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.5ktok/5.8kch
Ctx: est 157.5k/200.0k; warn 160.0k reload 190.0k; provider 321.3k


We might need to switch suddenly, big pickle is a free model and has low rate limits

Great catch again, fixed, please check


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Ctx: est 157.5k/200.0k; warn 160.0k reload 180.0k; provider 321.3k
Turn: i 760 o 275 t 355 cache 320.5k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Ctx: est 157.5k/200.0k; warn 160.0k reload 180.0k; provider 321.3k
Turn: i 760 o 275 t 355 cache 320.5k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.2s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Ctx: est 157.5k/200.0k; warn 160.0k reload 180.0k; provider 321.3k
Turn: i 760 o 275 t 355 cache 320.5k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.9s
Time: overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.6ktok/6.3kch
Ctx: est 157.5k/200.0k; warn 160.0k reload 180.0k; provider 321.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.9s
Time: model 5.0s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 80t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.6ktok/6.3kch
Ctx: est 157.5k/200.0k; warn 160.0k reload 180.0k; provider 321.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 14.0s
Time: model 11.1s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.6ktok/6.3kch
Ctx: est 159.1k/200.0k; warn 160.0k reload 180.0k; provider 321.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 20.1s
Time: model 17.2s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.6ktok/6.3kch
Ctx: est 159.1k/200.0k; warn 160.0k reload 180.0k; provider 321.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 26.1s
Time: model 23.2s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.6ktok/6.3kch
Ctx: est 159.1k/200.0k; warn 160.0k reload 180.0k; provider 321.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 32.1s
Time: model 29.2s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.6ktok/6.3kch
Ctx: est 159.1k/200.0k; warn 160.0k reload 180.0k; provider 321.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 38.2s
Time: model 35.3s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.6ktok/6.3kch
Ctx: est 159.1k/200.0k; warn 160.0k reload 180.0k; provider 321.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 44.3s
Time: model 41.4s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 760 o 275 t 355 cache 320.5k; p≈1.6ktok/6.3kch
Ctx: est 159.1k/200.0k; warn 160.0k reload 180.0k; provider 321.3k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 50.4s
Time: model 47.5s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 1.2k o 225 t 216 cache 325.6k; p≈1.6ktok/6.3kch
Ctx: est 159.3k/200.0k; warn 160.0k reload 180.0k; provider 326.9k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 51.6s
Time: model 48.7s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 1.2k o 225 t 216 cache 325.6k; p≈1.6ktok/6.3kch
Ctx: est 159.3k/200.0k; warn 160.0k reload 180.0k; provider 326.9k


This is a much better system now — the script was rewritten to be **model-aware**:

Great fix! The context guard script was rewritten. It now:

1. **Reads the model from the OpenCode config** (line 12, 169-195)
2. **Looks up the model's max context** from the provider definitions
3. **Calculates thresholds dynamically**: `warn = max_context × 0.80`, `reload = max_context × 0.90`
4. Falls back to env vars if explicitly set, but defaults to model-aware

So when DeepSeek V4 Flash (1M context) is active, it'll automatically set warn at 800K and reload at 900K. No more hardcoded 200K limit.

The guard JSON still shows 200K because the current session is on big-pickle which reports that as its max. It'll adjust automatically on the next reload with DeepSeek Flash. Clean solution! ✅


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 52.6s
Time: model 48.7s, overhead 4.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 1.2k o 225 t 216 cache 325.6k; p≈1.6ktok/6.3kch
Ctx: est 159.3k/200.0k; warn 160.0k reload 180.0k; provider 326.9k


Please record all the stuff that is useful in the future in your knowledge base, we will later look at this and the other ones and decide on a better approach with these examples


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Ctx: est 159.3k/200.0k; warn 160.0k reload 180.0k; provider 326.9k
Turn: i 1.2k o 225 t 216 cache 325.6k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Ctx: est 159.3k/200.0k; warn 160.0k reload 180.0k; provider 326.9k
Turn: i 1.2k o 225 t 216 cache 325.6k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.2s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Ctx: est 159.3k/200.0k; warn 160.0k reload 180.0k; provider 326.9k
Turn: i 1.2k o 225 t 216 cache 325.6k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 1.8s
Time: overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 1.2k o 225 t 216 cache 325.6k; p≈1.9ktok/7.5kch
Ctx: est 159.3k/200.0k; warn 160.0k reload 180.0k; provider 326.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.7s
Time: model 5.0s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 81t)
Turn: i 1.2k o 225 t 216 cache 325.6k; p≈1.9ktok/7.5kch
Ctx: est 159.3k/200.0k; warn 160.0k reload 180.0k; provider 326.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 13.8s
Time: model 11.1s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Turn: i 1.2k o 225 t 216 cache 325.6k; p≈1.9ktok/7.5kch
Ctx: est 161.1k/200.0k; warn 160.0k reload 180.0k; provider 326.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 19.9s
Time: model 17.1s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Turn: i 1.2k o 225 t 216 cache 325.6k; p≈1.9ktok/7.5kch
Ctx: est 161.1k/200.0k; warn 160.0k reload 180.0k; provider 326.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 26.0s
Time: model 23.2s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Turn: i 1.2k o 225 t 216 cache 325.6k; p≈1.9ktok/7.5kch
Ctx: est 161.1k/200.0k; warn 160.0k reload 180.0k; provider 326.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 32.1s
Time: model 29.4s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Turn: i 1.2k o 225 t 216 cache 325.6k; p≈1.9ktok/7.5kch
Ctx: est 161.1k/200.0k; warn 160.0k reload 180.0k; provider 326.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 38.2s
Time: model 35.4s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Turn: i 1.2k o 225 t 216 cache 325.6k; p≈1.9ktok/7.5kch
Ctx: est 161.3k/200.0k; warn 160.0k reload 180.0k; provider 326.9k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 40.3s
Time: model 37.5s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Turn: i 45 o 161 cache 330.8k; p≈1.9ktok/7.5kch
Ctx: est 161.3k/200.0k; warn 160.0k reload 180.0k; provider 330.8k


Done! Added 4 new entries to the knowledge base covering:

1. **Config mismatch risk** — model in wrapper vs opencode config can disagree, both need checking
2. **Context guard rewrite** — now model-aware, auto-calculates thresholds from model's max context
3. **Big-pickle discovery** — what model we were actually on, its traits (emoji style, verbose), rate limits, timeout behavior
4. **DeepSeek Flash switch** — confirmed ready for next reload with 1M context

55 entries total now across WGT, videoctl, matrix-lite, architecture, and knowledge-base. Good foundation for future sessions to build on. 🙂


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 41.4s
Time: model 37.5s, overhead 3.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Turn: i 45 o 161 cache 330.8k; p≈1.9ktok/7.5kch
Ctx: est 161.3k/200.0k; warn 160.0k reload 180.0k; provider 330.8k


We also need to check if the permissions are configured properly and will be picked up by the next session


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Ctx: est 161.3k/200.0k; warn 160.0k reload 180.0k; provider 330.8k
Turn: i 45 o 161 cache 330.8k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Ctx: est 161.3k/200.0k; warn 160.0k reload 180.0k; provider 330.8k
Turn: i 45 o 161 cache 330.8k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.2s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Ctx: est 161.3k/200.0k; warn 160.0k reload 180.0k; provider 330.8k
Turn: i 45 o 161 cache 330.8k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 2.1s
Time: overhead 2.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Turn: i 45 o 161 cache 330.8k; p≈1.8ktok/7.1kch
Ctx: est 161.3k/200.0k; warn 160.0k reload 180.0k; provider 330.8k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 8.0s
Time: model 5.0s, overhead 2.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 82t)
Turn: i 45 o 161 cache 330.8k; p≈1.8ktok/7.1kch
Ctx: est 161.3k/200.0k; warn 160.0k reload 180.0k; provider 330.8k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 14.3s
Time: model 11.3s, overhead 2.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Turn: i 45 o 161 cache 330.8k; p≈1.8ktok/7.1kch
Ctx: est 163.1k/200.0k; warn 160.0k reload 180.0k; provider 330.8k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 20.4s
Time: model 17.4s, overhead 2.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Turn: i 45 o 161 cache 330.8k; p≈1.8ktok/7.1kch
Ctx: est 163.1k/200.0k; warn 160.0k reload 180.0k; provider 330.8k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 26.4s
Time: model 23.4s, overhead 2.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Turn: i 45 o 161 cache 330.8k; p≈1.8ktok/7.1kch
Ctx: est 163.1k/200.0k; warn 160.0k reload 180.0k; provider 330.8k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 32.5s
Time: model 29.5s, overhead 2.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Turn: i 45 o 161 cache 330.8k; p≈1.8ktok/7.1kch
Ctx: est 163.1k/200.0k; warn 160.0k reload 180.0k; provider 330.8k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 38.5s
Time: model 35.5s, overhead 2.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Turn: i 45 o 161 cache 330.8k; p≈1.8ktok/7.1kch
Ctx: est 163.2k/200.0k; warn 160.0k reload 180.0k; provider 330.8k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 42.6s
Time: model 39.6s, overhead 2.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.8ktok/7.1kch
Ctx: est 163.3k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


The permissions are configured for the current agent, and a new session loads them fresh, so there shouldn't be a caching issue. Let me do a quick sanity check on the critical paths:Everything looks good for the next session. The preflight confirms the model switch command is allowed, and since it'll be a fresh session, it'll load the current config without caching issues.

Permissions are ready for the next session. No stale caching issue since a fresh session loads the config fresh. Key checks:

- ✅ Model switch command (`npx acpx set model *`) is allowed in the config
- ✅ Wrapper script has correct `OPENCODE_MODEL`
- ✅ Config file has `model: nano-gpt/deepseek/deepseek-v4-flash:thinking` in all sections
- ✅ Context guard will auto-adjust to 1M context

The switch should be seamless on next reload. If you need to switch before the natural reload (e.g., big-pickle rate limits get too painful), the `matrix_lite_status_switch_bot_model` tool can do it programmatically — it updates the wrapper script and reloads the session in one step.


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 43.8s
Time: model 39.6s, overhead 4.2s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.8ktok/7.1kch
Ctx: est 163.3k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


No, I mean the repo permissions. You still can't exec videoctl


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Ctx: est 163.3k/200.0k; warn 160.0k reload 180.0k; provider 333.9k
Turn: i 229 o 220 t 107 cache 333.7k


* ⚪ Queued
Stage: waiting for conversation turn
Model: opencode/big-pickle
Elapsed: 0.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Ctx: est 163.3k/200.0k; warn 160.0k reload 180.0k; provider 333.9k
Turn: i 229 o 220 t 107 cache 333.7k


* 🟡 Working
Stage: building prompt
Model: opencode/big-pickle
Elapsed: 1.2s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Ctx: est 163.3k/200.0k; warn 160.0k reload 180.0k; provider 333.9k
Turn: i 229 o 220 t 107 cache 333.7k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 2.0s
Time: overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.9ktok/7.6kch
Ctx: est 163.3k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 7.9s
Time: model 5.0s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 83t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.9ktok/7.6kch
Ctx: est 163.3k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 14.1s
Time: model 11.2s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.9ktok/7.6kch
Ctx: est 165.2k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 20.1s
Time: model 17.2s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.9ktok/7.6kch
Ctx: est 165.2k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 26.2s
Time: model 23.2s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.9ktok/7.6kch
Ctx: est 165.2k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 32.2s
Time: model 29.3s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.9ktok/7.6kch
Ctx: est 165.2k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 38.3s
Time: model 35.3s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.9ktok/7.6kch
Ctx: est 165.2k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 44.3s
Time: model 41.4s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.9ktok/7.6kch
Ctx: est 165.2k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 50.4s
Time: model 47.4s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.9ktok/7.6kch
Ctx: est 165.2k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 56.6s
Time: model 53.6s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 229 o 220 t 107 cache 333.7k; p≈1.9ktok/7.6kch
Ctx: est 165.2k/200.0k; warn 160.0k reload 180.0k; provider 333.9k


* 🟡 Working
Stage: model running
Model: opencode/big-pickle
Elapsed: 62.7s
Time: model 59.7s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 170 o 157 t 93 cache 341.9k; p≈1.9ktok/7.6kch
Ctx: est 165.4k/200.0k; warn 160.0k reload 180.0k; provider 342.1k


* 🟡 Processing result
Stage: model returned
Model: opencode/big-pickle
Elapsed: 63.8s
Time: model 60.9s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 170 o 157 t 93 cache 341.9k; p≈1.9ktok/7.6kch
Ctx: est 165.4k/200.0k; warn 160.0k reload 180.0k; provider 342.1k


Preflight confirms the config is correct — `/home/gleb/videoctl/bin/videoctl` is allowed. The reason it didn't work this session is the **startup permission caching issue** we identified earlier. The next session (fresh) will load the current config and should have videoctl access.

The findLast evaluation order in ACPX works in the allow's favor too — new videoctl allow (line 1538) comes after the old openclaw denys (line 391), so it wins.

So yes, next session should have full videoctl exec access. Want to do the reload now and test it, or wait for the natural session turnover?


* 🟢 Done
Stage: final reply sent
Model: opencode/big-pickle
Elapsed: 65.1s
Time: model 60.9s, overhead 4.2s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Turn: i 170 o 157 t 93 cache 341.9k; p≈1.9ktok/7.6kch
Ctx: est 165.4k/200.0k; warn 160.0k reload 180.0k; provider 342.1k


What about sfq-factory, automeat and matrix-lite? Is anything blocking there?


⚪ Received
Stage: queued for agent
Model: opencode/big-pickle
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 84t)
Ctx: est 165.4k/200.0k; warn 160.0k reload 180.0k; provider 342.1k
Turn: i 170 o 157 t 93 cache 341.9k