Model comparison
Claude Opus 5 vs GPT-5.1-Codex
Claude Opus 5 is the stronger model overall, scoring 67.8 to 38.6 on the Noometry Index. GPT-5.1-Codex costs 2.9× less per token, which makes it the better buy when Claude Opus 5's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Summary
- They share 3 benchmarks with published results for both. Claude Opus 5 scores higher in 3 categories and GPT-5.1-Codex in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Opus 5 leads 86.2 to 30.3.
- The biggest single-benchmark swing is ProofBench: 99% for Claude Opus 5 and 9% for GPT-5.1-Codex.
- GPT-5.1-Codex is cheaper at $1.25 / $10 per million input/output tokens, against $5 / $25 for Claude Opus 5.
- Claude Opus 5 accepts more context: 1M tokens versus 400K.
Side by side
| Claude Opus 5 | GPT-5.1-Codex | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 67.8 | 38.6 |
| Released | 2026-07-24 | 2025-11-12 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 400K |
| Max output | 128K | 128K |
| Input $ / M tokens | $5 | $1.25 |
| Output $ / M tokens | $25 | $10 |
| Results tracked | 57 | 6 |
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Category by category
Coding Claude Opus 5 leads
Claude Opus 5: 67.5 (#5), GPT-5.1-Codex: 41.9 (#116)
| Benchmark | Claude Opus 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena WebDev | 1691 | 1337 |
| ALE-Bench | 2,165 | 1,245 |
| DeepSWE | 73.6% | — |
| FrontierCode | 53.4% | — |
| SWE-bench Verified (bash only) | — | 66% |
| CursorBench | 46.6% | — |
| FrontierSWE | 52% | — |
| SciCode | 56.4% | — |
| WeirdML | 91.8% | — |
| LMArena Coding | 1534 | — |
Agentic & Tool Use Claude Opus 5 leads
Claude Opus 5: 55.6 (#1), GPT-5.1-Codex: 38.0 (#33)
| Benchmark | Claude Opus 5 | GPT-5.1-Codex |
|---|---|---|
| Terminal-Bench | — | 60.4% |
| APEX-Agents | 65.8% | — |
| OSWorld 2.0 | 31.4% | — |
| τ²-bench Banking | 48.7% | — |
| PostTrainBench | 35% | — |
| BALROG | 63.4% | — |
| GBAEval | 79.6% | — |
| GDP.pdf | 24% | — |
| METR Time Horizons | — | 70.8% |
| Vending-Bench 2 | 11,182 | — |
Reasoning Not comparable
Claude Opus 5: 77.2 (#4), GPT-5.1-Codex: —
| Benchmark | Claude Opus 5 | GPT-5.1-Codex |
|---|---|---|
| ARC-AGI-2 | 90.4% | — |
| SimpleBench | 80.6% | — |
| NYT Connections (extended) | 94.3% | — |
| ARC-AGI-1 | 97.5% | — |
| CritPt | 29.1% | — |
| Chess Puzzles | 42% | — |
| EBR-Bench | 45.7% | — |
| LMArena Hard Prompts | 1526 | — |
| Mystery Game Puzzles | 59% | — |
| DTBench | 97.9% | — |
| LMCA | 64.5% | — |
| Bench to the Future 3 | 0.12 | — |
| Epoch Capabilities Index | 162.78 | — |
Math Claude Opus 5 leads
Claude Opus 5: 86.2 (#8), GPT-5.1-Codex: 30.3 (#235)
| Benchmark | Claude Opus 5 | GPT-5.1-Codex |
|---|---|---|
| ProofBench | 99% | 9% |
| FrontierMath (Tiers 1-3) | 85.6% | — |
| FrontierMath Tier 4 | 73.2% | — |
| OTIS Mock AIME 2024-2025 | 98.9% | — |
| LMArena Math | 1531 | — |
Knowledge Not comparable
Claude Opus 5: 66.8 (#9), GPT-5.1-Codex: —
| Benchmark | Claude Opus 5 | GPT-5.1-Codex |
|---|---|---|
| GPQA Diamond | 93.9% | — |
| SimpleQA Verified | 59.9% | — |
| LMArena Expert | 1557 | — |
Multimodal Not comparable
Claude Opus 5: 50.8 (#8), GPT-5.1-Codex: —
| Benchmark | Claude Opus 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena Vision | 1319 | — |
| Blueprint-Bench 2 | 30.4% | — |
| Furniture Assembly | 60.8% | — |
| LMArena Document | 1516 | — |
Multilingual Not comparable
Claude Opus 5: 58.8 (#4), GPT-5.1-Codex: —
| Benchmark | Claude Opus 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena Non-English | 1501 | — |
| LMArena Chinese | 1574 | — |
| LMArena French | 1519 | — |
| LMArena German | 1524 | — |
| LMArena Japanese | 1516 | — |
| LMArena Korean | 1521 | — |
| LMArena Russian | 1507 | — |
| LMArena Spanish | 1519 | — |
Instruction Following Not comparable
Claude Opus 5: 79.2 (#7), GPT-5.1-Codex: —
| Benchmark | Claude Opus 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena Instruction Following | 1517 | — |
Long Context Not comparable
Claude Opus 5: 46.5 (#21), GPT-5.1-Codex: —
| Benchmark | Claude Opus 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena Longer Query | 1515 | — |
Writing & Preference Not comparable
Claude Opus 5: 79.2 (#1), GPT-5.1-Codex: —
| Benchmark | Claude Opus 5 | GPT-5.1-Codex |
|---|---|---|
| LMArena Text | 1507 | — |
| LMArena Creative Writing | 1491 | — |
| EQ-Bench Creative Writing | 2133 | — |
| EQ-Bench 4 | 1385 | — |
| LMArena Multi-Turn | 1499 | — |
Frequently asked questions
Is Claude Opus 5 better than GPT-5.1-Codex?
Claude Opus 5 is the stronger model overall, scoring 67.8 to 38.6 on the Noometry Index. GPT-5.1-Codex costs 2.9× less per token, which makes it the better buy when Claude Opus 5's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 5 or GPT-5.1-Codex?
GPT-5.1-Codex is cheaper. It lists at $1.25 per million input tokens and $10 per million output tokens; Claude Opus 5 lists at $5 and $25.
Is Claude Opus 5 or GPT-5.1-Codex better for coding?
Claude Opus 5 scores higher on coding benchmarks: 67.5 versus 41.9 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 5 does, with 1M tokens against 400K.
How many benchmarks do Claude Opus 5 and GPT-5.1-Codex share?
3 benchmarks have published results for both models. Claude Opus 5 has 57 scored results on Noometry and GPT-5.1-Codex has 6.