head-to-head
| Metric | GPT-5.6 Sol | Claude Fable 5 |
|---|---|---|
| SWE-bench Verified | 96.2% | 95.0% |
| SWE-bench Pro | — | 80.3% |
| Terminal-Bench | 88.8% | — |
| Input $ / 1M | $5 | $10 |
| Output $ / 1M | $30 | $50 |
| Context | — | 1M |
| Open weights | No | No |
| Access | API · Codex (public since Jul 9 2026) | API · Claude Code · Claude Cowork · claude.ai |
| Maker | OpenAI | Anthropic |
what do the benchmarks actually say?
On SWE-bench Verified — real, human-validated GitHub issues resolved end-to-end — GPT-5.6 Sol posts 96.2% against 95.0% for Claude Fable 5, a 1.2-point gap. Verified is the closest public proxy for "can it fix a real bug in a real repo without help", which is why it anchors our ranking.
A few points either way is real but not decisive: within that band, the agent scaffolding around the model — how it retrieves files, runs tests, and retries — often matters as much as the base model. Treat the gap as a lean, not a verdict.
which is cheaper to run?
GPT-5.6 Sol is the cheaper model: $5 per 1M input tokens ($30 output) versus $10 ($50 output) for Claude Fable 5 — roughly 2× less on input. Coding workloads are output-heavy — agents write diffs, tests and retries — so weight the output rate more than the input rate when you estimate a monthly bill.
when to pick each
The highest independently measured coding score of any model, and it holds up on the long tasks: 98% on the 1-to-4-hour tier where most models fall apart.
Mythos-class flagship for long-horizon agentic runs: the model to reach for when a task spans hours and hundreds of tool calls and has to actually finish.
how were these scores verified?
We only print a number once it's confirmed against a primary source or an independent evaluation, and each row on our leaderboard records which kind it is:
- GPT-5.6 Sol: Independent (vals.ai, Jul 14 2026, mini-swe-agent bash-only harness): SWE-bench Verified 96.20% ±0.86 — the top score on the board. Verified Jul 17, 2026; it had been unranked since Jun 26 because OpenAI published no SWE-bench number of its own, and it still has not. Read the #1 with care: the 1.2-point lead over Claude Fable 5 (95.00% ±0.98) is inside the combined margin of error (~0.9 sigma, not significant), so the two are a statistical tie and we rank Sol first only because it scored higher. Where it does separate is task length — 98% on 1-4 hour tasks vs 93% for Fable 5. OpenAI's own Terminal-Bench 2.1 claim is 88.8% (Sol) / 91.9% (Sol Ultra). No SWE-bench Pro score published. Pricing $5/$30 per 1M.
- Claude Fable 5: Independent (vals.ai, Jul 14 2026, mini-swe-agent bash-only harness): SWE-bench Verified 95.00% ±0.98. Held the top score until GPT-5.6 Sol was evaluated at 96.20% ±0.86 on the same harness — a 1.2-point gap that is inside the combined margin of error (~0.9 sigma), so the two are a statistical tie and we rank Sol first only because it scored higher. SWE-bench Pro 80.3% uses Anthropic's own scaffolding and is contested. Restored Jul 1, 2026 after a 20-day export-control suspension. Pricing $10/$50 per 1M.
Full reviewsGPT-5.6 Sol, decodedClaude Fable 5, decoded
Ranked on our AI Coding Leaderboard, updated 2026-07-17. Scores are confirmed against primary sources; prices are per 1M input tokens and can change.
- OpenAIvals.ai — SWE-bench Verified (independent) — Independent (vals.ai, Jul 14 2026, mini-swe-agent bash-only harness): SWE-bench Verified 96.20% ±0.86 — the top score on the board. Verified Jul 17, 2026; it had been unranked since Jun 26 because OpenAI published no SWE-bench number of its own, and it still has not. Read the #1 with care: the 1.2-point lead over Claude Fable 5 (95.00% ±0.98) is inside the combined margin of error (~0.9 sigma, not significant), so the two are a statistical tie and we rank Sol first only because it scored higher. Where it does separate is task length — 98% on 1-4 hour tasks vs 93% for Fable 5. OpenAI's own Terminal-Bench 2.1 claim is 88.8% (Sol) / 91.9% (Sol Ultra). No SWE-bench Pro score published. Pricing $5/$30 per 1M.
- AnthropicGENZ TECH — Claude Fable 5 returns — Independent (vals.ai, Jul 14 2026, mini-swe-agent bash-only harness): SWE-bench Verified 95.00% ±0.98. Held the top score until GPT-5.6 Sol was evaluated at 96.20% ±0.86 on the same harness — a 1.2-point gap that is inside the combined margin of error (~0.9 sigma), so the two are a statistical tie and we rank Sol first only because it scored higher. SWE-bench Pro 80.3% uses Anthropic's own scaffolding and is contested. Restored Jul 1, 2026 after a 20-day export-control suspension. Pricing $10/$50 per 1M.
- BenchmarkSWE-bench — the real-GitHub-issue benchmark