Model comparison
Claude Opus 4.8 vs GPT-5.1-Codex-mini
Claude Opus 4.8 has enough public results to be ranked (#13); GPT-5.1-Codex-mini does not yet, so treat this comparison as directional.
Last verified . 1 shared benchmarks.
Summary
- They share 1 benchmark with published results for both. Claude Opus 4.8 scores higher in 2 categories and GPT-5.1-Codex-mini in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where Claude Opus 4.8 leads 59.9 to 31.6.
- GPT-5.1-Codex-mini is cheaper at $0.25 / $2 per million input/output tokens, against $5 / $25 for Claude Opus 4.8.
- Claude Opus 4.8 accepts more context: 1M tokens versus 400K.
Side by side
| Claude Opus 4.8 | GPT-5.1-Codex-mini | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 60.7 | 37.3 |
| Released | 2026-05-28 | 2025-11-12 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 400K |
| Max output | 128K | 128K |
| Input $ / M tokens | $5 | $0.25 |
| Output $ / M tokens | $25 | $2 |
| Results tracked | 65 | 2 |
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Category by category
Coding Claude Opus 4.8 leads
Claude Opus 4.8: 59.9 (#12), GPT-5.1-Codex-mini: 31.6
| Benchmark | Claude Opus 4.8 | GPT-5.1-Codex-mini |
|---|---|---|
| LMArena WebDev | 1556 | 1244 |
| DeepSWE | 59% | — |
| FrontierCode | 46.5% | — |
| SciCode | 53.5% | — |
| GSO | 47.1% | — |
| WeirdML | 82.9% | — |
| LMArena Coding | 1490 | — |
| ALE-Bench | 1,564 | — |
Agentic & Tool Use Claude Opus 4.8 leads
Claude Opus 4.8: 47.6 (#11), GPT-5.1-Codex-mini: 38.5
| Benchmark | Claude Opus 4.8 | GPT-5.1-Codex-mini |
|---|---|---|
| Terminal-Bench | — | 61.6% |
| APEX-Agents | 48.9% | — |
| OSWorld 2.0 | 20.6% | — |
| Remote Labor Index | 8.3% | — |
| τ²-bench Banking | 39.7% | — |
| DeepResearch Bench | 50.2% | — |
| PostTrainBench | 33.8% | — |
| GBAEval | 70.9% | — |
| GDP.pdf | 24% | — |
| LMArena Search | 1204 | — |
| Vending-Bench 2 | 5,787 | — |
Reasoning Not comparable
Claude Opus 4.8: 64.7 (#16), GPT-5.1-Codex-mini: —
| Benchmark | Claude Opus 4.8 | GPT-5.1-Codex-mini |
|---|---|---|
| ARC-AGI-2 | 72.1% | — |
| SimpleBench | 64.8% | — |
| Kagi LLM Benchmark | 88.8% | — |
| NYT Connections (extended) | 91.1% | — |
| ARC-AGI-1 | 92.5% | — |
| CritPt | 20.9% | — |
| Chess Puzzles | 34% | — |
| EnigmaEval | 23.5% | — |
| EBR-Bench | 28.6% | — |
| LMArena Hard Prompts | 1482 | — |
| Mystery Game Puzzles | 36% | — |
| DTBench | 94.9% | — |
| LMCA | 57.5% | — |
| Surface Evolver Bench | 87.5% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 158.21 | — |
| ForecastBench | 59.9 | — |
Math Not comparable
Claude Opus 4.8: 78.4 (#13), GPT-5.1-Codex-mini: —
| Benchmark | Claude Opus 4.8 | GPT-5.1-Codex-mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | 80% | — |
| FrontierMath Tier 4 | 56.1% | — |
| MathArena Final-Answer Competitions | 91.8% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 69% | — |
| LMArena Math | 1487 | — |
| FrontierMath (Feb 2025 set) | 47.2% | — |
| FrontierMath Tier 4 (v1) | 31.3% | — |
Knowledge Not comparable
Claude Opus 4.8: 61.3 (#29), GPT-5.1-Codex-mini: —
| Benchmark | Claude Opus 4.8 | GPT-5.1-Codex-mini |
|---|---|---|
| GPQA Diamond | 91% | — |
| SimpleQA Verified | 53% | — |
| LMArena Expert | 1502 | — |
Multimodal Not comparable
Claude Opus 4.8: 42.9 (#26), GPT-5.1-Codex-mini: —
| Benchmark | Claude Opus 4.8 | GPT-5.1-Codex-mini |
|---|---|---|
| LMArena Vision | 1294 | — |
| Blueprint-Bench 2 | 14.5% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1475 | — |
Multilingual Not comparable
Claude Opus 4.8: 55.2 (#33), GPT-5.1-Codex-mini: —
| Benchmark | Claude Opus 4.8 | GPT-5.1-Codex-mini |
|---|---|---|
| LMArena Non-English | 1450 | — |
| LMArena Chinese | 1507 | — |
| LMArena French | 1481 | — |
| LMArena German | 1472 | — |
| LMArena Japanese | 1440 | — |
| LMArena Korean | 1432 | — |
| LMArena Russian | 1474 | — |
| LMArena Spanish | 1466 | — |
Instruction Following Not comparable
Claude Opus 4.8: 77.4 (#24), GPT-5.1-Codex-mini: —
| Benchmark | Claude Opus 4.8 | GPT-5.1-Codex-mini |
|---|---|---|
| LMArena Instruction Following | 1476 | — |
Long Context Not comparable
Claude Opus 4.8: 45.4 (#35), GPT-5.1-Codex-mini: —
| Benchmark | Claude Opus 4.8 | GPT-5.1-Codex-mini |
|---|---|---|
| LMArena Longer Query | 1483 | — |
Writing & Preference Not comparable
Claude Opus 4.8: 72.0 (#16), GPT-5.1-Codex-mini: —
| Benchmark | Claude Opus 4.8 | GPT-5.1-Codex-mini |
|---|---|---|
| LMArena Text | 1461 | — |
| LMArena Creative Writing | 1454 | — |
| EQ-Bench Creative Writing | 1840 | — |
| EQ-Bench 4 | 1281 | — |
| LMArena Multi-Turn | 1476 | — |
Frequently asked questions
Is Claude Opus 4.8 better than GPT-5.1-Codex-mini?
Claude Opus 4.8 has enough public results to be ranked (#13); GPT-5.1-Codex-mini does not yet, so treat this comparison as directional.
Which is cheaper, Claude Opus 4.8 or GPT-5.1-Codex-mini?
GPT-5.1-Codex-mini is cheaper. It lists at $0.25 per million input tokens and $2 per million output tokens; Claude Opus 4.8 lists at $5 and $25.
Is Claude Opus 4.8 or GPT-5.1-Codex-mini better for coding?
Claude Opus 4.8 scores higher on coding benchmarks: 59.9 versus 31.6 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 4.8 does, with 1M tokens against 400K.
How many benchmarks do Claude Opus 4.8 and GPT-5.1-Codex-mini share?
1 benchmark has published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and GPT-5.1-Codex-mini has 2.