Model comparison
Claude Opus 4.6 vs GPT-4.1
Claude Opus 4.6 is the stronger model overall, scoring 58.3 to 35.7 on the Noometry Index. GPT-4.1 costs 2.9× less per token, which makes it the better buy when Claude Opus 4.6's lead doesn't matter for your workload.
Last verified . 41 shared benchmarks.
Summary
- They share 41 benchmarks with published results for both. Claude Opus 4.6 scores higher in 9 categories and GPT-4.1 in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 4.6 leads 57.7 to 11.7.
- The biggest single-benchmark swing is ARC-AGI-1: 94% for Claude Opus 4.6 and 5.5% for GPT-4.1.
- GPT-4.1 is cheaper at $2 / $8 per million input/output tokens, against $5 / $25 for Claude Opus 4.6.
- GPT-4.1 accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Opus 4.6 | GPT-4.1 | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 58.3 | 35.7 |
| Released | 2026-02-04 | 2025-04-14 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 128K | 33K |
| Input $ / M tokens | $5 | $2 |
| Output $ / M tokens | $25 | $8 |
| Results tracked | 68 | 52 |
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Category by category
Coding Claude Opus 4.6 leads
Claude Opus 4.6: 57.7 (#15), GPT-4.1: 34.2 (#228)
| Benchmark | Claude Opus 4.6 | GPT-4.1 |
|---|---|---|
| SWE-bench Verified | 78.7% | 48.5% |
| SWE-bench Verified (bash only) | 75.6% | 39.6% |
| WeirdML | 78% | 39% |
| LMArena Coding | 1535 | 1391 |
| ALE-Bench | 996.5 | 558.1 |
| FrontierCode | 26.6% | — |
| Aider Polyglot | — | 52.4% |
| LMArena WebDev | 1546 | — |
| SWE-bench Multilingual | 72% | — |
| GSO | 41.2% | — |
| CadEval | — | 42% |
| AlgoTune | 1.47 | — |
Agentic & Tool Use Claude Opus 4.6 leads
Claude Opus 4.6: 51.0 (#4), GPT-4.1: 34.4 (#40)
| Benchmark | Claude Opus 4.6 | GPT-4.1 |
|---|---|---|
| Terminal-Bench | 79.8% | — |
| APEX-Agents | 46.3% | — |
| Berkeley Function Calling Leaderboard | — | 54% |
| Remote Labor Index | 4.2% | — |
| τ²-bench Banking | 27.3% | — |
| Cybench | 93% | — |
| DeepResearch Bench | 55.3% | — |
| GBAEval | 44.1% | — |
| LMArena Search | 1253 | — |
| METR Time Horizons | 78.9% | — |
| Vending-Bench 2 | 8,018 | — |
Reasoning Claude Opus 4.6 leads
Claude Opus 4.6: 57.7 (#21), GPT-4.1: 11.7 (#334)
| Benchmark | Claude Opus 4.6 | GPT-4.1 |
|---|---|---|
| ARC-AGI-2 | 69.2% | 0.4% |
| SimpleBench | 67.6% | 27% |
| Kagi LLM Benchmark | 83.6% | 52.3% |
| ARC-AGI-1 | 94% | 5.5% |
| Chess Puzzles | 17% | 6% |
| EnigmaEval | 7.6% | 2.2% |
| LMArena Hard Prompts | 1527 | 1384 |
| DTBench | 91.2% | 68.3% |
| LMCA | 55.8% | 25.6% |
| Epoch Capabilities Index | 155.36 | 136.79 |
| ForecastBench | 60 | 61.5 |
| NYT Connections (extended) | 92.1% | — |
| Thematic Generalization | 80.6% | — |
| EBR-Bench | 12.7% | — |
| Mystery Game Puzzles | 25% | — |
Math Claude Opus 4.6 leads
Claude Opus 4.6: 62.7 (#25), GPT-4.1: 21.4 (#269)
| Benchmark | Claude Opus 4.6 | GPT-4.1 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 66% | 6% |
| OTIS Mock AIME 2024-2025 | 94.4% | 38.3% |
| LMArena Math | 1517 | 1369 |
| FrontierMath (Feb 2025 set) | 40.7% | 5.5% |
| FrontierMath Tier 4 (v1) | 22.9% | 0% |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 78.5% | — |
| ProofBench | 50% | — |
| Omni-MATH | — | 47.1% |
| MATH Level 5 | — | 83% |
Knowledge Claude Opus 4.6 leads
Claude Opus 4.6: 61.8 (#23), GPT-4.1: 37.0 (#152)
| Benchmark | Claude Opus 4.6 | GPT-4.1 |
|---|---|---|
| GPQA Diamond | 90.5% | 66.9% |
| Humanity's Last Exam | 34.4% | 5.4% |
| SimpleQA Verified | 47% | 31.1% |
| Vectara Hallucination Rate | 12.2% | 5.6% |
| LMArena Expert | 1546 | 1364 |
| MMLU-Pro | — | 81.1% |
| GPQA (HELM) | — | 65.9% |
Multimodal Too close to call
Claude Opus 4.6: 37.0 (#67), GPT-4.1: 37.5 (#66)
| Benchmark | Claude Opus 4.6 | GPT-4.1 |
|---|---|---|
| LMArena Vision | 1316 | 1210 |
| GeoBench | — | 72% |
| Furniture Assembly | 28.3% | — |
| LMArena Document | 1507 | — |
Multilingual Claude Opus 4.6 leads
Claude Opus 4.6: 58.2 (#4), GPT-4.1: 49.6 (#128)
| Benchmark | Claude Opus 4.6 | GPT-4.1 |
|---|---|---|
| LMArena Non-English | 1490 | 1370 |
| LMArena Chinese | 1551 | 1382 |
| LMArena French | 1513 | 1383 |
| LMArena German | 1504 | 1380 |
| LMArena Japanese | 1484 | 1320 |
| LMArena Korean | 1465 | 1339 |
| LMArena Russian | 1497 | 1377 |
| LMArena Spanish | 1512 | 1375 |
Instruction Following Claude Opus 4.6 leads
Claude Opus 4.6: 79.7 (#3), GPT-4.1: 71.5 (#148)
| Benchmark | Claude Opus 4.6 | GPT-4.1 |
|---|---|---|
| LMArena Instruction Following | 1523 | 1367 |
| IFEval | — | 83.8% |
Long Context Claude Opus 4.6 leads
Claude Opus 4.6: 48.1 (#13), GPT-4.1: 40.0 (#158)
| Benchmark | Claude Opus 4.6 | GPT-4.1 |
|---|---|---|
| LMArena Longer Query | 1520 | 1385 |
| Fiction.LiveBench | — | 63.9% |
| CL-bench | 20.7% | — |
| CL-bench Life | 17% | — |
Writing & Preference Claude Opus 4.6 leads
Claude Opus 4.6: 73.7 (#9), GPT-4.1: 57.8 (#120)
| Benchmark | Claude Opus 4.6 | GPT-4.1 |
|---|---|---|
| LMArena Text | 1504 | 1383 |
| LMArena Creative Writing | 1506 | 1363 |
| EQ-Bench Creative Writing | 1809 | 1420 |
| LMArena Multi-Turn | 1514 | 1398 |
| WildBench | — | 85.4% |
| EQ-Bench 4 | 1223 | — |
Frequently asked questions
Is Claude Opus 4.6 better than GPT-4.1?
Claude Opus 4.6 is the stronger model overall, scoring 58.3 to 35.7 on the Noometry Index. GPT-4.1 costs 2.9× less per token, which makes it the better buy when Claude Opus 4.6's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4.6 or GPT-4.1?
GPT-4.1 is cheaper. It lists at $2 per million input tokens and $8 per million output tokens; Claude Opus 4.6 lists at $5 and $25.
Is Claude Opus 4.6 or GPT-4.1 better for coding?
Claude Opus 4.6 scores higher on coding benchmarks: 57.7 versus 34.2 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 does, with 1.05M tokens against 1M.
How many benchmarks do Claude Opus 4.6 and GPT-4.1 share?
41 benchmarks have published results for both models. Claude Opus 4.6 has 68 scored results on Noometry and GPT-4.1 has 52.