Model comparison
GPT-4.1 nano vs GPT-5.1
GPT-5.1 is the stronger model overall, scoring 48.8 to 27.7 on the Noometry Index. GPT-4.1 nano costs 20× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Last verified . 32 shared benchmarks.
Summary
- They share 32 benchmarks with published results for both. GPT-4.1 nano scores higher in 0 categories and GPT-5.1 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.1 leads 39.9 to 8.6.
- The biggest single-benchmark swing is ARC-AGI-1: 0% for GPT-4.1 nano and 72.8% for GPT-5.1.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-4.1 nano | GPT-5.1 | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 27.7 | 48.8 |
| Released | 2025-04-14 | 2025-11-13 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 33K | 128K |
| Input $ / M tokens | $0.10 | $1.25 |
| Output $ / M tokens | $0.40 | $10 |
| Results tracked | 38 | 63 |
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Category by category
Coding GPT-5.1 leads
GPT-4.1 nano: 23.8 (#325), GPT-5.1: 46.9 (#59)
| Benchmark | GPT-4.1 nano | GPT-5.1 |
|---|---|---|
| SciCode | 25.9% | 43.3% |
| WeirdML | 19% | 60.8% |
| LMArena Coding | 1306 | 1454 |
| SWE-bench Verified | — | 68% |
| SWE-bench Verified (bash only) | — | 66% |
| Aider Polyglot | 8.9% | — |
| LMArena WebDev | — | 1395 |
| GSO | — | 13.7% |
| LiveBench Coding | — | 72.5% |
| ALE-Bench | — | 1,192 |
Agentic & Tool Use GPT-5.1 leads
GPT-4.1 nano: 26.3 (#98), GPT-5.1: 32.5 (#55)
| Benchmark | GPT-4.1 nano | GPT-5.1 |
|---|---|---|
| Terminal-Bench | — | 47.6% |
| Berkeley Function Calling Leaderboard | 33% | — |
| DeepResearch Bench | — | 42.8% |
| LMArena Search | — | 1199 |
| Vending-Bench 2 | — | 1,473 |
Reasoning GPT-5.1 leads
GPT-4.1 nano: 8.6 (#344), GPT-5.1: 39.9 (#50)
| Benchmark | GPT-4.1 nano | GPT-5.1 |
|---|---|---|
| ARC-AGI-2 | 0% | 17.6% |
| ARC-AGI-1 | 0% | 72.8% |
| CritPt | 0% | 4.9% |
| LMArena Hard Prompts | 1286 | 1457 |
| DTBench | 52.5% | 90.1% |
| LMCA | 5.5% | 43.9% |
| Epoch Capabilities Index | 129.62 | 149.66 |
| SimpleBench | — | 53.2% |
| Kagi LLM Benchmark | 33.3% | — |
| Chess Puzzles | — | 32% |
| EnigmaEval | — | 11.2% |
| LiveBench Reasoning | — | 95.8% |
| Mystery Game Puzzles | — | 19% |
| LiveBench Data Analysis | — | 72.1% |
| ForecastBench | — | 58.1 |
| LiveBench | — | 78.8% |
Math GPT-5.1 leads
GPT-4.1 nano: 25.5 (#246), GPT-5.1: 50.3 (#45)
| Benchmark | GPT-4.1 nano | GPT-5.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 28.9% | 88.6% |
| Omni-MATH | 36.7% | 46.4% |
| LMArena Math | 1274 | 1446 |
| FrontierMath (Feb 2025 set) | 1% | 31% |
| LiveBench Math | — | 94.5% |
| MATH Level 5 | 70% | — |
| FrontierMath Tier 4 (v1) | — | 12.5% |
Knowledge GPT-5.1 leads
GPT-4.1 nano: 21.8 (#268), GPT-5.1: 50.5 (#65)
| Benchmark | GPT-4.1 nano | GPT-5.1 |
|---|---|---|
| GPQA Diamond | 48.9% | 87.6% |
| SimpleQA Verified | 6% | 48% |
| MMLU-Pro | 55% | 57.9% |
| GPQA (HELM) | 50.7% | 44.2% |
| LMArena Expert | 1272 | 1470 |
| Humanity's Last Exam | — | 23.7% |
| Vectara Hallucination Rate | — | 10.9% |
Multimodal GPT-5.1 leads
GPT-4.1 nano: 28.6 (#108), GPT-5.1: 44.0 (#17)
| Benchmark | GPT-4.1 nano | GPT-5.1 |
|---|---|---|
| LMArena Vision | 1063 | 1250 |
| VPCT | — | 58.7% |
| LMArena Document | — | 1403 |
Multilingual GPT-5.1 leads
GPT-4.1 nano: 41.8 (#200), GPT-5.1: 54.0 (#51)
| Benchmark | GPT-4.1 nano | GPT-5.1 |
|---|---|---|
| LMArena Non-English | 1260 | 1431 |
| LMArena Chinese | 1270 | 1495 |
| LMArena German | 1288 | 1439 |
| LMArena Japanese | 1199 | 1453 |
| LMArena Russian | 1261 | 1435 |
| LMArena French | — | 1451 |
| LMArena Korean | — | 1401 |
| LMArena Spanish | — | 1430 |
Instruction Following GPT-5.1 leads
GPT-4.1 nano: 68.0 (#188), GPT-5.1: 84.0 (#1)
| Benchmark | GPT-4.1 nano | GPT-5.1 |
|---|---|---|
| IFEval | 84.3% | 93.5% |
| LMArena Instruction Following | 1267 | 1442 |
| LiveBench Instruction Following | — | 93.3% |
Long Context GPT-5.1 leads
GPT-4.1 nano: 23.7 (#291), GPT-5.1: 47.6 (#14)
| Benchmark | GPT-4.1 nano | GPT-5.1 |
|---|---|---|
| LMArena Longer Query | 1283 | 1448 |
| Fiction.LiveBench | 25% | — |
| CL-bench | — | 23.7% |
| CL-bench Life | — | 17.3% |
Writing & Preference GPT-5.1 leads
GPT-4.1 nano: 40.7 (#238), GPT-5.1: 64.7 (#53)
| Benchmark | GPT-4.1 nano | GPT-5.1 |
|---|---|---|
| LMArena Text | 1285 | 1443 |
| LMArena Creative Writing | 1260 | 1427 |
| WildBench | 81.2% | 86.3% |
| LMArena Multi-Turn | 1277 | 1449 |
| EQ-Bench Creative Writing | 946 | — |
| LiveBench Language | — | 80.2% |
Frequently asked questions
Is GPT-4.1 nano better than GPT-5.1?
GPT-5.1 is the stronger model overall, scoring 48.8 to 27.7 on the Noometry Index. GPT-4.1 nano costs 20× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or GPT-5.1?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GPT-4.1 nano or GPT-5.1 better for coding?
GPT-5.1 scores higher on coding benchmarks: 46.9 versus 23.8 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 400K.
How many benchmarks do GPT-4.1 nano and GPT-5.1 share?
32 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and GPT-5.1 has 63.