Model comparison
GPT-4 vs GPT-4.1 nano
GPT-4 is the stronger model overall, scoring 28.9 to 27.7 on the Noometry Index. GPT-4.1 nano costs 214× less per token, which makes it the better buy when GPT-4's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. GPT-4 scores higher in 3 categories and GPT-4.1 nano in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-4.1 nano leads 25.5 to 10.1.
- The biggest single-benchmark swing is MATH Level 5: 23% for GPT-4 and 70% for GPT-4.1 nano.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $30 / $60 for GPT-4.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 8K.
Side by side
| GPT-4 | GPT-4.1 nano | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 28.9 | 27.7 |
| Released | 2023-03-14 | 2025-04-14 |
| Weights | Proprietary | Proprietary |
| Context window | 8K | 1.05M |
| Max output | 8K | 33K |
| Input $ / M tokens | $30 | $0.10 |
| Output $ / M tokens | $60 | $0.40 |
| Results tracked | 38 | 38 |
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Category by category
Coding GPT-4 leads
GPT-4: 31.2 (#277), GPT-4.1 nano: 23.8 (#325)
| Benchmark | GPT-4 | GPT-4.1 nano |
|---|---|---|
| WeirdML | 12.4% | 19% |
| LMArena Coding | 1254 | 1306 |
| Aider Polyglot | — | 8.9% |
| SciCode | — | 25.9% |
| BigCodeBench Instruct | 46% | — |
| BigCodeBench Complete | 57.2% | — |
| HumanEval+ | 79.3% | — |
Agentic & Tool Use Not comparable
GPT-4: —, GPT-4.1 nano: 26.3 (#98)
| Benchmark | GPT-4 | GPT-4.1 nano |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 33% |
| METR Time Horizons | 36.1% | — |
Reasoning GPT-4 leads
GPT-4: 17.3 (#285), GPT-4.1 nano: 8.6 (#344)
| Benchmark | GPT-4 | GPT-4.1 nano |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1286 |
| DTBench | 62.7% | 52.5% |
| LMCA | 17.1% | 5.5% |
| Epoch Capabilities Index | 125.88 | 129.62 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 33.3% |
| ARC-AGI-1 | — | 0% |
| CritPt | — | 0% |
| Chess Puzzles | 4% | — |
| Mystery Game Puzzles | 12% | — |
| BIG-Bench Hard | 75.1% | — |
| ForecastBench | 57.8 | — |
| HellaSwag | 95.3% | — |
| WinoGrande | 87.5% | — |
Math GPT-4.1 nano leads
GPT-4: 10.1 (#304), GPT-4.1 nano: 25.5 (#246)
| Benchmark | GPT-4 | GPT-4.1 nano |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.1% | 28.9% |
| LMArena Math | 1269 | 1274 |
| MATH Level 5 | 23% | 70% |
| Omni-MATH | — | 36.7% |
| FrontierMath (Feb 2025 set) | — | 1% |
| GSM8K | 92% | — |
Knowledge GPT-4.1 nano leads
GPT-4: 18.4 (#277), GPT-4.1 nano: 21.8 (#268)
| Benchmark | GPT-4 | GPT-4.1 nano |
|---|---|---|
| GPQA Diamond | 35.7% | 48.9% |
| LMArena Expert | 1211 | 1272 |
| SimpleQA Verified | — | 6% |
| MMLU-Pro | — | 55% |
| GPQA (HELM) | — | 50.7% |
| MMLU | 86.4% | — |
| TriviaQA | 84.8% | — |
Multimodal Not comparable
GPT-4: —, GPT-4.1 nano: 28.6 (#108)
| Benchmark | GPT-4 | GPT-4.1 nano |
|---|---|---|
| LMArena Vision | — | 1063 |
Multilingual GPT-4.1 nano leads
GPT-4: 40.8 (#210), GPT-4.1 nano: 41.8 (#200)
| Benchmark | GPT-4 | GPT-4.1 nano |
|---|---|---|
| LMArena Non-English | 1246 | 1260 |
| LMArena Chinese | 1242 | 1270 |
| LMArena German | 1251 | 1288 |
| LMArena Japanese | 1209 | 1199 |
| LMArena Russian | 1251 | 1261 |
| LMArena French | 1282 | — |
| LMArena Korean | 1184 | — |
| LMArena Spanish | 1261 | — |
Instruction Following GPT-4.1 nano leads
GPT-4: 65.5 (#217), GPT-4.1 nano: 68.0 (#188)
| Benchmark | GPT-4 | GPT-4.1 nano |
|---|---|---|
| LMArena Instruction Following | 1241 | 1267 |
| IFEval | — | 84.3% |
Long Context GPT-4 leads
GPT-4: 37.7 (#207), GPT-4.1 nano: 23.7 (#291)
| Benchmark | GPT-4 | GPT-4.1 nano |
|---|---|---|
| LMArena Longer Query | 1244 | 1283 |
| Fiction.LiveBench | — | 25% |
Writing & Preference GPT-4.1 nano leads
GPT-4: 35.0 (#263), GPT-4.1 nano: 40.7 (#238)
| Benchmark | GPT-4 | GPT-4.1 nano |
|---|---|---|
| LMArena Text | 1263 | 1285 |
| LMArena Creative Writing | 1244 | 1260 |
| EQ-Bench Creative Writing | 752 | 946 |
| LMArena Multi-Turn | 1257 | 1277 |
| WildBench | — | 81.2% |
Frequently asked questions
Is GPT-4 better than GPT-4.1 nano?
GPT-4 is the stronger model overall, scoring 28.9 to 27.7 on the Noometry Index. GPT-4.1 nano costs 214× less per token, which makes it the better buy when GPT-4's lead doesn't matter for your workload.
Which is cheaper, GPT-4 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; GPT-4 lists at $30 and $60.
Is GPT-4 or GPT-4.1 nano better for coding?
GPT-4 scores higher on coding benchmarks: 31.2 versus 23.8 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 8K.
How many benchmarks do GPT-4 and GPT-4.1 nano share?
22 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and GPT-4.1 nano has 38.