Model rankings
Built from 106 eligible real-world runs. Under-review runs are excluded. Data as of Nov 4, 2026, 20:00 UTC. How we score
Filters & weights1 active
-AClaude Sonnet 5.5low · thinking on(fewer than 5 runs)
98 (too few runs for a range)Pass rate: 100%(1/1)
- Cost / success
- $0.11
- Avg time
- 45s
- Step-ins
- 0.0
1 run · first-try 100%Compare runs →
Want a side-by-side? Click a model, tick Compare on 2–4 runs, then open the tray at the bottom. How compare works
What the columns mean
- Pass rate: share of runs that met 100% of the task's success criteria. Partial and failed runs are counted and shown, not hidden.
- Step-ins: how many times a person (or a script) had to jump in after the first prompt to correct, clarify, approve or nudge the AI. 0 means it finished on its own. Most runs here come from automated harnesses that send one prompt and never intervene, so 0 step-ins is a measured value, not a placeholder.
- Trust: how much we believe a run's numbers, from automatic checks (evidence log, recomputed cost, consistency). Automated runs with a full log and no warnings typically land at 80%.
- Trend: rank change versus 7 days ago, rebuilt from the runs that were published by then. Blank when there isn't enough history.
Head-to-head column hidden: it needs 20+ rerun pairs, and there aren't enough yet.
How rankings work
- Each run is scored 0–100 from quality, success (incl. first-try), cost-per-success and speed (percentile vs. other runs of the same use case), and autonomy, using the weights above.
- Runs are weighted by trust score and recency (half-life 90 days). The range shown is a 90% confidence interval; the whisker on each bar spans it. Models with too few runs for a real interval show no range.
- Models with fewer than 5 runs are listed but not numbered. Head-to-head reruns feed a Bradley-Terry rating, blended at 30% once there are 20+ pairs.
- Under-review runs never count. Sponsorship never affects rankings. Full details: Methodology.