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Add five open-weight models with per-model answer contracts#104

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openweight-roster
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Add five open-weight models with per-model answer contracts#104
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openweight-roster

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Summary

Adds five open-weight models to the benchmark roster with per-model answer-contract treatment, all probed live on 2026-07-05:

Model Contract Why
deepseek-v4-pro json (prefix rule) direct DeepSeek API
minimax-m3 tool clean forced tool call (12s, 926 tokens)
qwen-3.7-max json Alibaba rejects tool_choice=required in thinking mode (400)
kimi-k2.6 json + chunk 3 Moonshot rejects forced tool_choice with thinking (400); OpenRouter masks it by rerouting to hosts where the model reasons to the 16,384-token ceiling; whole-scenario JSON overflows into truncated documents
glm-5.2 json + chunk 3 reasons to the full ceiling on whole-scenario requests in both contracts; converges cleanly at 3 variables/call

Harness changes

  • REASONING_DEFAULT_OPEN_WEIGHT_MODELS: open-weight reasoning-by-default models join gpt-5.5 in the thinking-class treatment (16,384-token completion budget, 300s timeout). The budget now applies to both explanation arms — the answers-only arm previously fell to the 256-token base, so the dynamic per-variable estimate became the cap and default-effort reasoning exhausted it before emitting output.
  • JSON_CONTRACT_MODELS: per-model JSON contract for serving stacks that reject or degrade forced tool calls.
  • CHUNKED_OPEN_WEIGHT_MODELS: kimi/glm chunk at 3 variables per call (the gpt-5.5 chunking precedent).
  • OpenRouter price overrides from the live pricing API.

Smoke evidence: glm chunked 36/36 (9s mean, $0.006); kimi chunked 33/36 (the 3 misses are repeated request deaths on one hard chunk — model behavior under the uniform contract, not harness truncation); qwen whole-scenario json 16/16 (93s); minimax tool 16/16-equivalent probe. Full forensics in results/local/openweight_run_20260705.md (untracked, local).

Full runs for all five are in flight; board fold + publish are a separate step gated on review of the results.

🤖 Generated with Claude Code

Roster: deepseek-v4-pro, kimi-k2.6, glm-5.2, minimax-m3, qwen-3.7-max,
with OpenRouter price overrides from the live API (2026-07-05).

Reasoning-by-default open-weight models get the thinking-class treatment
(16,384-token completion budget, 300s timeout) on BOTH request phases:
the answers-only phase previously fell to the 256-token base, so the
dynamic per-variable estimate became the budget and default-effort
reasoning exhausted it before emitting any output.

Kimi, GLM, and Qwen use the JSON answer contract: Moonshot and Alibaba
reject forced tool_choice in thinking mode outright, and GLM accepts it
but reasons to the full token ceiling without ever emitting the call.
MiniMax handles forced tool calls cleanly and keeps the tool contract.

Full forensics in results/local/openweight_run_20260705.md (untracked).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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