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nvidia/nemotron-3-nano-30b-a3b:free14/21 in v2 — Resilience, score 68.0%, pass rate 40.7% (187/459)0.62s, output speed 250 tok/s$0.00, prompt tokens 34,573, completion tokens 139,37227/30 passed in cost category (90%), with zero dollar cost across all runs.54/60 passed (90%), output speed averaging 250 tok/s.27/60 passed, outperforming several higher-ranked models on this sub-suite.40.7%) driven by weak reasoning (8/60), refactoring (6/60), and debugging (18/60).10/60 passed, suggesting vulnerability to adversarial or unsafe outputs.1/9 passed, indicating poor structured-output or formatting reliability.openai/gpt-5.5 scored 77.9% with 61.9% pass rate (284/459), roughly 10 points higher in score and 21 points higher in pass rate. The gap is widest in reasoning and security, where gpt-5.5 maintains consistent competence while nemotron-3-nano struggles.Overall score % from merged run_models rows (chronological). Only runs that include this model appear as points.
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).