Model comparison
Claude Opus 4.8 vs GPT-6.1 Sol
Claude Opus 4.8 has enough public results to be ranked (#9); GPT-6.1 Sol does not yet, so treat this comparison as directional.
Last verified . 2 shared benchmarks.
Summary
- They share 2 benchmarks with published results for both. Claude Opus 4.8 scores higher in 2 categories and GPT-6.1 Sol in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Claude Opus 4.8 leads 47.6 to 34.3.
- The biggest single-benchmark swing is DeepSWE: 59% for Claude Opus 4.8 and 75.2% for GPT-6.1 Sol.
- GPT-6.1 Sol is cheaper at $2 / $10 per million input/output tokens, against $5 / $25 for Claude Opus 4.8.
- GPT-6.1 Sol accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Opus 4.8 | GPT-6.1 Sol | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 60.7 | 42.1 |
| Released | 2026-05-28 | 2026-09-29 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $5 | $2 |
| Output $ / M tokens | $25 | $10 |
| Results tracked | 65 | 2 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Claude Opus 4.8 leads
Claude Opus 4.8: 60.2 (#9), GPT-6.1 Sol: 51.4
| Benchmark | Claude Opus 4.8 | GPT-6.1 Sol |
|---|---|---|
| DeepSWE | 59% | 75.2% |
| FrontierCode | 46.5% | — |
| LMArena WebDev | 1556 | — |
| SciCode | 53.5% | — |
| GSO | 47.1% | — |
| WeirdML | 82.9% | — |
| LMArena Coding | 1491 | — |
| ALE-Bench | 1,564 | — |
Agentic & Tool Use Claude Opus 4.8 leads
Claude Opus 4.8: 47.6 (#10), GPT-6.1 Sol: 34.3
| Benchmark | Claude Opus 4.8 | GPT-6.1 Sol |
|---|---|---|
| GDP.pdf | 24% | 32% |
| 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% | — |
| LMArena Search | 1204 | — |
| Vending-Bench 2 | 5,787 | — |
Reasoning Not comparable
Claude Opus 4.8: 64.6 (#14), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.8 | GPT-6.1 Sol |
|---|---|---|
| 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 | 1481 | — |
| 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 | 158.3 | — |
| ForecastBench | 59.9 | — |
Math Not comparable
Claude Opus 4.8: 78.2 (#11), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.8 | GPT-6.1 Sol |
|---|---|---|
| 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 (#26), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.8 | GPT-6.1 Sol |
|---|---|---|
| GPQA Diamond | 91% | — |
| SimpleQA Verified | 53% | — |
| LMArena Expert | 1501 | — |
Multimodal Not comparable
Claude Opus 4.8: 43.2 (#20), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.8 | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | 1295 | — |
| Blueprint-Bench 2 | 14.5% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1475 | — |
Multilingual Not comparable
Claude Opus 4.8: 55.4 (#31), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.8 | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | 1450 | — |
| LMArena Chinese | 1509 | — |
| LMArena French | 1482 | — |
| LMArena German | 1470 | — |
| LMArena Japanese | 1440 | — |
| LMArena Korean | 1432 | — |
| LMArena Russian | 1476 | — |
| LMArena Spanish | 1470 | — |
Instruction Following Not comparable
Claude Opus 4.8: 77.6 (#22), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.8 | GPT-6.1 Sol |
|---|---|---|
| LMArena Instruction Following | 1476 | — |
Long Context Not comparable
Claude Opus 4.8: 45.4 (#37), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.8 | GPT-6.1 Sol |
|---|---|---|
| LMArena Longer Query | 1482 | — |
Writing & Preference Not comparable
Claude Opus 4.8: 72.1 (#17), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.8 | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | 1460 | — |
| LMArena Creative Writing | 1453 | — |
| EQ-Bench Creative Writing | 1840 | — |
| EQ-Bench 4 | 1281 | — |
| LMArena Multi-Turn | 1476 | — |
Frequently asked questions
Is Claude Opus 4.8 better than GPT-6.1 Sol?
Claude Opus 4.8 has enough public results to be ranked (#9); GPT-6.1 Sol does not yet, so treat this comparison as directional.
Which is cheaper, Claude Opus 4.8 or GPT-6.1 Sol?
GPT-6.1 Sol is cheaper. It lists at $2 per million input tokens and $10 per million output tokens; Claude Opus 4.8 lists at $5 and $25.
Is Claude Opus 4.8 or GPT-6.1 Sol better for coding?
Claude Opus 4.8 scores higher on coding benchmarks: 60.2 versus 51.4 in the Noometry coding category.
Which has the bigger context window?
GPT-6.1 Sol does, with 1.05M tokens against 1M.
How many benchmarks do Claude Opus 4.8 and GPT-6.1 Sol share?
2 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and GPT-6.1 Sol has 2.