llm
- Tabby turned file contents into numbers
TabbyAPI's qwen3_coder parser runs every tool argument through json.loads and strip(). A string "123" arrives as 123, and file content loses its edges.
- The models deleted the benchmark's log
Coding agents found the harness's live log in their workspace, read it as another agent's run, and deleted it. Three rows recorded zero tool calls.
- LFM2.5 is fast. Gemma 4 finishes the job
LFM2.5-24B-A2B vs Gemma 4 26B-A4B as local coding agents, 3 runs per task: LFM wins on speed; on Spring Boot only Gemma wrote tests.
- 2.2x faster prefill, 1.04x faster agent
A new engine prefilled 2.1-2.2x faster than llama.cpp at every depth. Driving a coding agent, it finished 4% sooner. The server logs say where the speed went.
- The engine got credit for the quant
open-jet beat llama.cpp 7 to 3 on a Zig agent task. On open-jet's own GGUF, llama.cpp went 7 of 9 too. Only the speed gap belonged to the engine.
- My benchmark served the model at half speed
The launcher turned on MTP drafting for five models. The benchmark's own server script didn't, and its result rows had no field that could show it.
- My benchmark read my CLAUDE.md
An audit built to check sampler overrides found my OpenCode bench runs carrying my global ~/.claude/CLAUDE.md and skills: 53,483 characters of prompt.
- Zig needed context, not time
Four 27B local models kept hitting the one-hour wall on a Zig task. Four hours at 64k got 7 of 12 through the core tests. At 128k, 35 of 36 did, cleanly.
- The deadlock test can't see a half-held lock
Every model wrote a thread test. Most of them could not fail: with locks taken in id order, opposite-direction transfers serialize on one mutex.
- Zig's defer ends at the closing brace
A local model locked two accounts in the right order, scored 97/100, and lost money. One Zig defer sat inside an if block and unlocked at the brace.