Model comparison
GPT-4.1 nano vs GPT-4o mini
GPT-4.1 nano is the stronger model overall, scoring 27.7 to 25.4 on the Noometry Index.
Last verified . 32 shared benchmarks.
Summary
- They share 32 benchmarks with published results for both. GPT-4.1 nano scores higher in 6 categories and GPT-4o mini in 4 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-4.1 nano leads 25.5 to 9.9.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 28.9% for GPT-4.1 nano and 6.9% for GPT-4o mini.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.15 / $0.60 for GPT-4o mini.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 128K.
Side by side
| GPT-4.1 nano | GPT-4o mini | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 27.7 | 25.4 |
| Released | 2025-04-14 | 2024-07-18 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 128K |
| Max output | 33K | 16K |
| Input $ / M tokens | $0.10 | $0.15 |
| Output $ / M tokens | $0.40 | $0.60 |
| Results tracked | 38 | 60 |
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Category by category
Coding GPT-4.1 nano leads
GPT-4.1 nano: 23.8 (#325), GPT-4o mini: 21.6 (#330)
| Benchmark | GPT-4.1 nano | GPT-4o mini |
|---|---|---|
| Aider Polyglot | 8.9% | 3.6% |
| WeirdML | 19% | 11.8% |
| LMArena Coding | 1306 | 1290 |
| SciCode | 25.9% | — |
| BigCodeBench Instruct | — | 46.1% |
| LiveBench Coding | — | 43.1% |
| BigCodeBench Complete | — | 57.4% |
| HumanEval+ | — | 83.5% |
| MBPP+ | — | 72.2% |
Agentic & Tool Use Too close to call
GPT-4.1 nano: 26.3 (#98), GPT-4o mini: 27.2 (#95)
| Benchmark | GPT-4.1 nano | GPT-4o mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | 33% | — |
| BALROG | — | 17.4% |
Reasoning Too close to call
GPT-4.1 nano: 8.6 (#344), GPT-4o mini: 8.7 (#343)
| Benchmark | GPT-4.1 nano | GPT-4o mini |
|---|---|---|
| ARC-AGI-2 | 0% | 0% |
| Kagi LLM Benchmark | 33.3% | 28.8% |
| LMArena Hard Prompts | 1286 | 1267 |
| DTBench | 52.5% | 54.4% |
| LMCA | 5.5% | 10.4% |
| Epoch Capabilities Index | 129.62 | 126.56 |
| SimpleBench | — | 10.7% |
| ARC-AGI-1 | 0% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | — | 32.8% |
| Mystery Game Puzzles | — | 12% |
| LiveBench Data Analysis | — | 50% |
| LiveBench | — | 41.3% |
| PIQA | — | 88.7% |
Math GPT-4.1 nano leads
GPT-4.1 nano: 25.5 (#246), GPT-4o mini: 9.9 (#307)
| Benchmark | GPT-4.1 nano | GPT-4o mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 28.9% | 6.9% |
| Omni-MATH | 36.7% | 28% |
| LMArena Math | 1274 | 1267 |
| MATH Level 5 | 70% | 52.6% |
| FrontierMath (Tiers 1-3) | — | 0.7% |
| LiveBench Math | — | 36.3% |
| FrontierMath (Feb 2025 set) | 1% | — |
| GSM8K | — | 91.3% |
Knowledge GPT-4.1 nano leads
GPT-4.1 nano: 21.8 (#268), GPT-4o mini: 17.7 (#279)
| Benchmark | GPT-4.1 nano | GPT-4o mini |
|---|---|---|
| GPQA Diamond | 48.9% | 37.7% |
| SimpleQA Verified | 6% | 8.3% |
| MMLU-Pro | 55% | 60.3% |
| GPQA (HELM) | 50.7% | 36.8% |
| LMArena Expert | 1272 | 1235 |
| Confabulations | — | 37.2% |
| BoolQ | — | 88.7% |
| MMLU | — | 81.8% |
Multimodal GPT-4.1 nano leads
GPT-4.1 nano: 28.6 (#108), GPT-4o mini: 25.3 (#117)
| Benchmark | GPT-4.1 nano | GPT-4o mini |
|---|---|---|
| LMArena Vision | 1063 | 1066 |
| Video-MME | — | 64.8% |
| GeoBench | — | 64% |
| VPCT | — | 34% |
Multilingual Too close to call
GPT-4.1 nano: 41.8 (#200), GPT-4o mini: 42.2 (#194)
| Benchmark | GPT-4.1 nano | GPT-4o mini |
|---|---|---|
| LMArena Non-English | 1260 | 1266 |
| LMArena Chinese | 1270 | 1264 |
| LMArena German | 1288 | 1272 |
| LMArena Japanese | 1199 | 1216 |
| LMArena Russian | 1261 | 1275 |
| LMArena French | — | 1296 |
| LMArena Korean | — | 1195 |
| LMArena Spanish | — | 1276 |
Instruction Following GPT-4.1 nano leads
GPT-4.1 nano: 68.0 (#188), GPT-4o mini: 62.1 (#234)
| Benchmark | GPT-4.1 nano | GPT-4o mini |
|---|---|---|
| IFEval | 84.3% | 78.2% |
| LMArena Instruction Following | 1267 | 1259 |
| LiveBench Instruction Following | — | 56.8% |
Long Context GPT-4o mini leads
GPT-4.1 nano: 23.7 (#291), GPT-4o mini: 39.1 (#181)
| Benchmark | GPT-4.1 nano | GPT-4o mini |
|---|---|---|
| LMArena Longer Query | 1283 | 1289 |
| Fiction.LiveBench | 25% | — |
Writing & Preference GPT-4.1 nano leads
GPT-4.1 nano: 40.7 (#238), GPT-4o mini: 39.7 (#243)
| Benchmark | GPT-4.1 nano | GPT-4o mini |
|---|---|---|
| LMArena Text | 1285 | 1286 |
| LMArena Creative Writing | 1260 | 1268 |
| EQ-Bench Creative Writing | 946 | 873 |
| WildBench | 81.2% | 79.1% |
| LMArena Multi-Turn | 1277 | 1285 |
| Short-Story Creative Writing | — | 67.2% |
| LiveBench Language | — | 28.6% |
Frequently asked questions
Is GPT-4.1 nano better than GPT-4o mini?
GPT-4.1 nano is the stronger model overall, scoring 27.7 to 25.4 on the Noometry Index.
Which is cheaper, GPT-4.1 nano or GPT-4o mini?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GPT-4o mini lists at $0.15 and $0.60.
Is GPT-4.1 nano or GPT-4o mini better for coding?
GPT-4.1 nano scores higher on coding benchmarks: 23.8 versus 21.6 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4.1 nano and GPT-4o mini share?
32 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and GPT-4o mini has 60.