Add qwen3.8-max benchmark scores to model-scores.yaml - #24
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Research and add static fallback scores for qwen3.8-max (Go/Paid tier) which was missing from LiveBench and the static fallback. Scores sourced from BenchLM.ai (verified benchmark aggregation): - coding: 77.0 (#6/130, 96th percentile) - instruction_following: 93.9 (#2/33, 97th percentile) - overall: 78.2 (#6/215) - reasoning: 95.5 (#1/2, 100th percentile) - vision: 88.1 (#2/34, 97th percentile, multimodal) Corroborated by evolink.ai vendor benchmark analysis. Closes#23
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Co-authored-by: dianlight <dianlight@users.noreply.github.com>
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Summary
The maintenance audit (issue #23) identified
qwen3.8-maxas missing score data from LiveBench and the static fallback inconfig/model-scores.yaml.Research
Searched the web for benchmark scores for
qwen3.8-max(Go/Paid tier). Found verified benchmark data from BenchLM.ai (independent benchmark aggregation, 52 source-displayable rows):Corroborated by evolink.ai vendor benchmark analysis (Qwen3.8-Max release package, Aug 3 2026): Terminal-Bench 2.1: 86.6, SWE-bench Pro: 67.7, IFBench: 82.8, HLE: 43.6.
Changes
qwen3.8-maxentry toconfig/model-scores.yamlwith scores on the 0-100 scale consistent with existing entries.Verification
python scripts/opencode_maintenance.py— runs clean; "All models have scores, no stale fallback entries"ruff check scripts/— all checks passedyamllint config/model-scores.yaml— no errorsCloses#23