Model comparison
Claude Sonnet 4.6 vs GPT-4.1 nano
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 27.9 on the Noometry Index. GPT-4.1 nano costs 34× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.
Last verified . 28 shared benchmarks.
Summary
- They share 28 benchmarks with published results for both. Claude Sonnet 4.6 scores higher in 10 categories and GPT-4.1 nano in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Sonnet 4.6 leads 46.1 to 8.5.
- The biggest single-benchmark swing is ARC-AGI-1: 86.5% for Claude Sonnet 4.6 and 0% for GPT-4.1 nano.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.6.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Sonnet 4.6 | GPT-4.1 nano | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 50.3 | 27.9 |
| Released | 2026-02-17 | 2025-04-14 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 128K | 33K |
| Input $ / M tokens | $3 | $0.10 |
| Output $ / M tokens | $15 | $0.40 |
| Results tracked | 57 | 38 |
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Category by category
Coding Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.3 (#67), GPT-4.1 nano: 24.1 (#330)
| Benchmark | Claude Sonnet 4.6 | GPT-4.1 nano |
|---|---|---|
| SciCode | 46.8% | 25.9% |
| WeirdML | 66.1% | 19% |
| LMArena Coding | 1504 | 1306 |
| SWE-bench Verified | 75.2% | — |
| DeepSWE | 29.9% | — |
| FrontierCode | 24.3% | — |
| Aider Polyglot | — | 8.9% |
| LMArena WebDev | 1522 | — |
| ALE-Bench | 1,327 | — |
Agentic & Tool Use Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 39.1 (#28), GPT-4.1 nano: 26.5 (#104)
| Benchmark | Claude Sonnet 4.6 | GPT-4.1 nano |
|---|---|---|
| Terminal-Bench | 53.4% | — |
| APEX-Agents | 43% | — |
| Berkeley Function Calling Leaderboard | — | 33% |
| OSWorld 2.0 | 9.3% | — |
| DeepResearch Bench | 54.9% | — |
| OSWorld | 72.1% | — |
| ExploitBench | 23.6% | — |
| GBAEval | 48.8% | — |
| GDP.pdf | 18% | — |
| LMArena Search | 1221 | — |
| Vending-Bench 2 | 7,204 | — |
Reasoning Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.1 (#45), GPT-4.1 nano: 8.5 (#349)
| Benchmark | Claude Sonnet 4.6 | GPT-4.1 nano |
|---|---|---|
| ARC-AGI-2 | 60.4% | 0% |
| ARC-AGI-1 | 86.5% | 0% |
| CritPt | 3.1% | 0% |
| LMArena Hard Prompts | 1484 | 1286 |
| DTBench | 89.9% | 52.5% |
| LMCA | 46.5% | 5.5% |
| Epoch Capabilities Index | 152.24 | 129.62 |
| Kagi LLM Benchmark | — | 33.3% |
| NYT Connections (extended) | 80.9% | — |
| Chess Puzzles | 13% | — |
| Thematic Generalization | 76.3% | — |
| Mystery Game Puzzles | 16% | — |
| ForecastBench | 62 | — |
Math Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 52.9 (#49), GPT-4.1 nano: 26.9 (#252)
| Benchmark | Claude Sonnet 4.6 | GPT-4.1 nano |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 85.8% | 28.9% |
| LMArena Math | 1462 | 1274 |
| FrontierMath (Feb 2025 set) | 32.4% | 1% |
| ProofBench | 45% | — |
| Omni-MATH | — | 36.7% |
| MATH Level 5 | — | 70% |
| FrontierMath Tier 4 (v1) | 8.3% | — |
Knowledge Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 51.7 (#65), GPT-4.1 nano: 21.8 (#273)
| Benchmark | Claude Sonnet 4.6 | GPT-4.1 nano |
|---|---|---|
| GPQA Diamond | 87.4% | 48.9% |
| SimpleQA Verified | 35.5% | 6% |
| LMArena Expert | 1500 | 1272 |
| MMLU-Pro | — | 55% |
| Vectara Hallucination Rate | 10.6% | — |
| GPQA (HELM) | — | 50.7% |
Multimodal Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 38.0 (#68), GPT-4.1 nano: 29.2 (#113)
| Benchmark | Claude Sonnet 4.6 | GPT-4.1 nano |
|---|---|---|
| LMArena Vision | 1283 | 1063 |
| Blueprint-Bench 2 | 6.7% | — |
| LMArena Document | 1482 | — |
Multilingual Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 54.4 (#41), GPT-4.1 nano: 41.6 (#205)
| Benchmark | Claude Sonnet 4.6 | GPT-4.1 nano |
|---|---|---|
| LMArena Non-English | 1440 | 1260 |
| LMArena Chinese | 1491 | 1270 |
| LMArena German | 1428 | 1288 |
| LMArena Japanese | 1420 | 1198 |
| LMArena Russian | 1440 | 1261 |
| LMArena French | 1465 | — |
| LMArena Korean | 1411 | — |
| LMArena Spanish | 1464 | — |
Instruction Following Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 77.4 (#25), GPT-4.1 nano: 67.8 (#193)
| Benchmark | Claude Sonnet 4.6 | GPT-4.1 nano |
|---|---|---|
| LMArena Instruction Following | 1475 | 1267 |
| IFEval | — | 84.3% |
Long Context Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 45.3 (#44), GPT-4.1 nano: 23.7 (#296)
| Benchmark | Claude Sonnet 4.6 | GPT-4.1 nano |
|---|---|---|
| LMArena Longer Query | 1479 | 1283 |
| Fiction.LiveBench | — | 25% |
Writing & Preference Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 70.2 (#22), GPT-4.1 nano: 40.5 (#243)
| Benchmark | Claude Sonnet 4.6 | GPT-4.1 nano |
|---|---|---|
| LMArena Text | 1458 | 1285 |
| LMArena Creative Writing | 1435 | 1260 |
| EQ-Bench Creative Writing | 1810 | 946 |
| LMArena Multi-Turn | 1464 | 1277 |
| WildBench | — | 81.2% |
| EQ-Bench 4 | 1207 | — |
Frequently asked questions
Is Claude Sonnet 4.6 better than GPT-4.1 nano?
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 27.9 on the Noometry Index. GPT-4.1 nano costs 34× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 4.6 or GPT-4.1 nano?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Claude Sonnet 4.6 lists at $3 and $15.
Is Claude Sonnet 4.6 or GPT-4.1 nano better for coding?
Claude Sonnet 4.6 scores higher on coding benchmarks: 46.3 versus 24.1 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 1M.
How many benchmarks do Claude Sonnet 4.6 and GPT-4.1 nano share?
28 benchmarks have published results for both models. Claude Sonnet 4.6 has 57 scored results on Noometry and GPT-4.1 nano has 38.