AA-Briefcase
We haven't written a description for this benchmark yet; see the card notes below for how each maker ran it.
- ModelScoreYour cost / mo
- 1Claude Opus 5 · Anthropicbest value1720 Elo
- 2Claude Fable 5.1 · Anthropic1694 Elo
- 3Grok 4.6 · xAIbest value1577 Elo
- 4Mistral Large 4 · Mistral AIbest value1393 Elo
“Best value”: no other model here reports a higher score at a lower cost for your workload. Scores are self-reported by each maker with different settings, so treat close calls as ties.
How each maker reported it
- Claude Opus 5 Table 8.1.A, p.148–149
Claude Opus 5 results use adaptive thinking at max effort, averaged over five trials (ARC-AGI-3 at high effort). GPT-5.6 Sol's FrontierBench figure uses Codex and its ARC-AGI-1 figure is at xhigh. The Fable 5 HealthBench Professional figure carries a footnote reading "Mythos 5". Competitor figures come from the developers' own published results or leaderboards.
- Claude Fable 5.1 Table 8.1.A, p.167
Fable 5.1 and Mythos 5.1 share weights, so column 0 covers both (likewise Fable 5 / Mythos 5). Claude results use adaptive thinking at max effort, averaged over five trials. Terminal-Bench 4.0 values are from §8.6, p.171 (Mythos 5.1: 60.9%; GPT-5.6 Sol from the public leaderboard). Competitor figures come from the developers' own published results or leaderboards.
- Grok 4.6 §2–7, p.7–28
Grok models at high effort (EEBench Grok 4.6 xhigh is 60.0%). Competitors at max effort (Fable 5 with fallback); GPT-5.6 Sol at xhigh on APEX-SWE and CADGenBench, high on DeepSearchQA. Most results come from third-party evaluators, each with its own harness. CyberGym is run without production safeguards.
- Mistral Large 4 launch post
Preliminary, vendor-reported preview results. Many charts in the post give no numbers; only figures stated in text are listed. Blind human coding eval run by Surge AI on a 1–5 scale.
Only each model's own maker's number is shown; scores a maker reports for rival models are left out.