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mistralai/mistral-medium-3-511/28 + score 62.0% + pass rate 59.9% (498/832)0.34s + output speed 194.4 tok/s$1.33, prompt tokens 56904, completion tokens 16804675% pass rate, 90/120 passed).9/9) and coding_ui (6/6).28/30 cost tests passed).43.4% pass rate, 53/122).37.5% pass rate, 45/120).57.5% pass rate, 69/120).qwen/qwen3.6-flash by ~21% score and ~23% pass rate.x-ai/grok-4.20 (79.1% score) and ~openai/gpt-mini-latest (78.3%).Suitable for low-stakes UI/hallucination-sensitive tasks; avoid for complex reasoning or refactoring. Deployment risk is moderate due to inconsistent category performance.
Overall score % from merged run_models rows (chronological). Only runs that include this model appear as points.
Overall score % from the most recent run per selected suite version for this model. Different suites use different fixtures and max scores — only interpret comparisons qualitatively.
No score samples for the selected versions.
Score % vs pass rate % per category. With 0/1 scorers, both usually line up; with proportional tests, score % reflects partial credit while pass rate counts tests that clear the fixture threshold.
Total estimated spend per scope for this model (bars, left axis) and mean spend per merged result row (line, right axis: total ÷ tests).
Pass rate % per difficulty level — complements the score % view above.
Normalized 0–100 within this model: TTFT (shorter → higher spoke) and decode tok/s (higher → higher spoke). Values come from streamed BLXBench runs merged into overall_ranking.json.
Pass rate % per category for this model (distinct from score %, which reflects partial credit).