Intent-Classification
Bonsai 2 vs Qwen3.8-27B on an RTX 3090: Speed Doubled, Scope Broke
Bonsai 2 27B, PrismML's ternary Qwen3.8, on a 3090: 1.8x the decode of Q4 from a 7.2 GB file, then 12 of 47 against 19 on a routing split. One field broke.
Jev Mode on a 3090: 26 ms per Token You Don't Write
Jev-style parallel decisions in llama.cpp on Qwen3.6-27B, RTX 3090: 1.3x faster at four tokens, 5.5x at fifty, 21 vs 23 of 47. The gain is the tokens you skip.
LoRA Skill Compilation Is a Double-Headed Coin Flip
Ten LoRA seeds on identical data spread 3.62 points, against 4.65 for prompt compilation. Not one beat the no-adapter base. Measured on an RTX 3090.
I Got the AI Result I Wanted. Then I Ran It Nine More Times
A frontier model read my logs and wrote a skill that beat my local 27B baseline by 10.6 points. Nine more compilation runs showed the number was fake.
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