Model comparison
Claude Opus 4.6 vs GPT-6.1 Sol
Claude Opus 4.6 has enough public results to be ranked (#18); GPT-6.1 Sol does not yet, so treat this comparison as directional.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in agentic & tool use, where Claude Opus 4.6 leads 51.0 to 34.3.
- GPT-6.1 Sol is cheaper at $2 / $10 per million input/output tokens, against $5 / $25 for Claude Opus 4.6.
- GPT-6.1 Sol accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Opus 4.6 | GPT-6.1 Sol | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 58.3 | 42.1 |
| Released | 2026-02-04 | 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 | 68 | 2 |
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Category by category
Coding Claude Opus 4.6 leads
Claude Opus 4.6: 57.7 (#15), GPT-6.1 Sol: 51.4
| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| SWE-bench Verified | 78.7% | — |
| DeepSWE | — | 75.2% |
| FrontierCode | 26.6% | — |
| SWE-bench Verified (bash only) | 75.6% | — |
| LMArena WebDev | 1546 | — |
| SWE-bench Multilingual | 72% | — |
| GSO | 41.2% | — |
| WeirdML | 78% | — |
| LMArena Coding | 1535 | — |
| ALE-Bench | 996.5 | — |
| AlgoTune | 1.47 | — |
Agentic & Tool Use Claude Opus 4.6 leads
Claude Opus 4.6: 51.0 (#4), GPT-6.1 Sol: 34.3
| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| Terminal-Bench | 79.8% | — |
| APEX-Agents | 46.3% | — |
| Remote Labor Index | 4.2% | — |
| τ²-bench Banking | 27.3% | — |
| Cybench | 93% | — |
| DeepResearch Bench | 55.3% | — |
| GBAEval | 44.1% | — |
| GDP.pdf | — | 32% |
| LMArena Search | 1253 | — |
| METR Time Horizons | 78.9% | — |
| Vending-Bench 2 | 8,018 | — |
Reasoning Not comparable
Claude Opus 4.6: 57.7 (#21), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| ARC-AGI-2 | 69.2% | — |
| SimpleBench | 67.6% | — |
| Kagi LLM Benchmark | 83.6% | — |
| NYT Connections (extended) | 92.1% | — |
| ARC-AGI-1 | 94% | — |
| Chess Puzzles | 17% | — |
| EnigmaEval | 7.6% | — |
| Thematic Generalization | 80.6% | — |
| EBR-Bench | 12.7% | — |
| LMArena Hard Prompts | 1527 | — |
| Mystery Game Puzzles | 25% | — |
| DTBench | 91.2% | — |
| LMCA | 55.8% | — |
| Epoch Capabilities Index | 155.36 | — |
| ForecastBench | 60 | — |
Math Not comparable
Claude Opus 4.6: 62.7 (#25), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | 66% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 78.5% | — |
| OTIS Mock AIME 2024-2025 | 94.4% | — |
| ProofBench | 50% | — |
| LMArena Math | 1517 | — |
| FrontierMath (Feb 2025 set) | 40.7% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |
Knowledge Not comparable
Claude Opus 4.6: 61.8 (#23), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| GPQA Diamond | 90.5% | — |
| Humanity's Last Exam | 34.4% | — |
| SimpleQA Verified | 47% | — |
| Vectara Hallucination Rate | 12.2% | — |
| LMArena Expert | 1546 | — |
Multimodal Not comparable
Claude Opus 4.6: 37.0 (#67), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | 1316 | — |
| Furniture Assembly | 28.3% | — |
| LMArena Document | 1507 | — |
Multilingual Not comparable
Claude Opus 4.6: 58.2 (#4), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | 1490 | — |
| LMArena Chinese | 1551 | — |
| LMArena French | 1513 | — |
| LMArena German | 1504 | — |
| LMArena Japanese | 1484 | — |
| LMArena Korean | 1465 | — |
| LMArena Russian | 1497 | — |
| LMArena Spanish | 1512 | — |
Instruction Following Not comparable
Claude Opus 4.6: 79.7 (#3), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| LMArena Instruction Following | 1523 | — |
Long Context Not comparable
Claude Opus 4.6: 48.1 (#13), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| CL-bench | 20.7% | — |
| CL-bench Life | 17% | — |
| LMArena Longer Query | 1520 | — |
Writing & Preference Not comparable
Claude Opus 4.6: 73.7 (#9), GPT-6.1 Sol: —
| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | 1504 | — |
| LMArena Creative Writing | 1506 | — |
| EQ-Bench Creative Writing | 1809 | — |
| EQ-Bench 4 | 1223 | — |
| LMArena Multi-Turn | 1514 | — |
Frequently asked questions
Is Claude Opus 4.6 better than GPT-6.1 Sol?
Claude Opus 4.6 has enough public results to be ranked (#18); GPT-6.1 Sol does not yet, so treat this comparison as directional.
Which is cheaper, Claude Opus 4.6 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 4.6 lists at $5 and $25.
Is Claude Opus 4.6 or GPT-6.1 Sol better for coding?
Claude Opus 4.6 scores higher on coding benchmarks: 57.7 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 4.6 and GPT-6.1 Sol share?
0 benchmarks have published results for both models. Claude Opus 4.6 has 68 scored results on Noometry and GPT-6.1 Sol has 2.