Pass rate
Tasks solved / tasks in scope, up to 2 attempts (strict per-set denominator).
Formula: (tasks_passed_attempt_1 + tasks_passed_attempt_2_only) / task_set_size
Includes unattempted tasks as failures. Scope-aware; reflects active filters (set, category, difficulty). Primary ranking metric.
Avg cost / task
Average LLM cost per distinct benchmark task in USD.
Formula: SUM(cost_usd) / COUNT(DISTINCT task_id) across all the model's results in scope.
Use to compare operating cost across models with similar pass rates. Does not account for quality. Combine with $/Pass for a cost-efficiency view.
Latency p50
Median per-task wall time (LLM call + compile + test), in milliseconds.
Formula: 50th percentile of per-task duration_ms: LLM latency + compile time + test time.
Use p50 for a typical-case latency expectation. Unaffected by outlier slow tasks.
Avg attempt score
Mean per-attempt score on a 0–100 point scale (partial credit). Drill-down only.
Formula: Mean of attempt scores across all results rows: SUM(score) / COUNT(*) over the results table. Each attempt earns 0–100 points based on compile + test outcomes.
Drill-down companion to pass_at_n. Rewards partial credit but not directly comparable to pass rate; use for within-model analysis.
All-runs pass rate
Fraction of tasks the model solved in every single run (strict consistency, also written pass^n).
Formula: tasks where ALL runs produced a passing result / tasks_attempted_distinct
Measures reliability under repetition. High value means the model is unlikely to regress on a re-run, important for CI and production use. Formal name in the literature: pass^n.
$/Pass
Total cost divided by number of distinct tasks passed. Lower is better.
Formula: SUM(cost_usd) / tasks_passed_distinct across all runs.
Best single cost-efficiency metric. Penalises expensive models that pass few tasks and rewards cheap models with high pass rates.
Latency p95
95th-percentile per-task wall time. Captures tail latency.
Formula: 95th percentile of per-task duration_ms across all tasks in all runs.
Use p95 to understand worst-case latency. A low p95 means the model rarely stalls, relevant for automated pipelines with timeouts.
Overview
Qwen: Qwen3.6 35B A3B has run on 0 occasions, attempting 0 tasks with an average score of 0.0 / 100.
Settings
Generation parameters used across this model's runs. "varies" indicates the value differed between runs.
- Temperature
- varies
- Thinking budget
- varies
- Avg tokens / run (input + output)
- —
- Consistency
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History
No runs yet.
Cost
No cost data yet.
Shortcomings
AL concepts Qwen: Qwen3.6 35B A3B struggles with. Click a row for description, correct pattern, and observed error codes.
Shortcomings analysis queued
Queued for analysis. This section will populate once the run is processed.
Recent runs
| Started | Run | Model | Tasks | Score | Cost | Duration | Status |
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Methodology
Pass rate counts unattempted tasks as failures (strict denominator). Avg score is the mean of every attempt the model produced — failed first tries that triggered a retry contribute one observation each, pulling the mean down. See the about page for the full breakdown and unit conventions.