Model comparison
GPT-4.1 nano vs MiniMax M1
MiniMax M1 is the stronger model overall, scoring 40.3 to 27.9 on the Noometry Index. GPT-4.1 nano costs 5.5× less per token, which makes it the better buy when MiniMax M1's lead doesn't matter for your workload.
Last verified . 15 shared benchmarks.
MiniMaxSummary
- They share 15 benchmarks with published results for both. GPT-4.1 nano scores higher in 0 categories and MiniMax M1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where MiniMax M1 leads 26.9 to 8.5.
- The biggest single-benchmark swing is Fiction.LiveBench: 25% for GPT-4.1 nano and 69.4% for MiniMax M1.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.55 / $2.20 for MiniMax M1.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 1M.
- MiniMax M1 has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 nano | MiniMax M1 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Noometry Index | 27.9 | 40.3 |
| Released | 2025-04-14 | 2025-06-13 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 1M |
| Max output | 33K | 40K |
| Input $ / M tokens | $0.10 | $0.55 |
| Output $ / M tokens | $0.40 | $2.20 |
| Results tracked | 38 | 18 |
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Category by category
Coding MiniMax M1 leads
GPT-4.1 nano: 24.1 (#330), MiniMax M1: 39.9 (#153)
| Benchmark | GPT-4.1 nano | MiniMax M1 |
|---|---|---|
| LMArena Coding | 1306 | 1359 |
| Aider Polyglot | 8.9% | — |
| SciCode | 25.9% | — |
| WeirdML | 19% | — |
Agentic & Tool Use Not comparable
GPT-4.1 nano: 26.5 (#104), MiniMax M1: —
| Benchmark | GPT-4.1 nano | MiniMax M1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 33% | — |
Reasoning MiniMax M1 leads
GPT-4.1 nano: 8.5 (#349), MiniMax M1: 26.9 (#126)
| Benchmark | GPT-4.1 nano | MiniMax M1 |
|---|---|---|
| LMArena Hard Prompts | 1286 | 1339 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 33.3% | — |
| ARC-AGI-1 | 0% | — |
| CritPt | 0% | — |
| DTBench | 52.5% | — |
| LMCA | 5.5% | — |
| Epoch Capabilities Index | 129.62 | — |
Math MiniMax M1 leads
GPT-4.1 nano: 26.9 (#252), MiniMax M1: 37.5 (#151)
| Benchmark | GPT-4.1 nano | MiniMax M1 |
|---|---|---|
| LMArena Math | 1274 | 1361 |
| OTIS Mock AIME 2024-2025 | 28.9% | — |
| Omni-MATH | 36.7% | — |
| MATH Level 5 | 70% | — |
| FrontierMath (Feb 2025 set) | 1% | — |
Knowledge MiniMax M1 leads
GPT-4.1 nano: 21.8 (#273), MiniMax M1: 36.4 (#170)
| Benchmark | GPT-4.1 nano | MiniMax M1 |
|---|---|---|
| LMArena Expert | 1272 | 1317 |
| GPQA Diamond | 48.9% | — |
| SimpleQA Verified | 6% | — |
| MMLU-Pro | 55% | — |
| GPQA (HELM) | 50.7% | — |
Multimodal Not comparable
GPT-4.1 nano: 29.2 (#113), MiniMax M1: —
| Benchmark | GPT-4.1 nano | MiniMax M1 |
|---|---|---|
| LMArena Vision | 1063 | — |
Multilingual MiniMax M1 leads
GPT-4.1 nano: 41.6 (#205), MiniMax M1: 45.8 (#163)
| Benchmark | GPT-4.1 nano | MiniMax M1 |
|---|---|---|
| LMArena Non-English | 1260 | 1319 |
| LMArena Chinese | 1270 | 1360 |
| LMArena German | 1288 | 1350 |
| LMArena Japanese | 1198 | 1217 |
| LMArena Russian | 1261 | 1329 |
| LMArena French | — | 1370 |
| LMArena Korean | — | 1266 |
| LMArena Spanish | — | 1353 |
Instruction Following MiniMax M1 leads
GPT-4.1 nano: 67.8 (#193), MiniMax M1: 69.3 (#174)
| Benchmark | GPT-4.1 nano | MiniMax M1 |
|---|---|---|
| LMArena Instruction Following | 1267 | 1312 |
| IFEval | 84.3% | — |
Long Context MiniMax M1 leads
GPT-4.1 nano: 23.7 (#296), MiniMax M1: 41.4 (#141)
| Benchmark | GPT-4.1 nano | MiniMax M1 |
|---|---|---|
| Fiction.LiveBench | 25% | 69.4% |
| LMArena Longer Query | 1283 | 1326 |
Writing & Preference MiniMax M1 leads
GPT-4.1 nano: 40.5 (#243), MiniMax M1: 53.1 (#161)
| Benchmark | GPT-4.1 nano | MiniMax M1 |
|---|---|---|
| LMArena Text | 1285 | 1343 |
| LMArena Creative Writing | 1260 | 1298 |
| LMArena Multi-Turn | 1277 | 1335 |
| EQ-Bench Creative Writing | 946 | — |
| WildBench | 81.2% | — |
Frequently asked questions
Is GPT-4.1 nano better than MiniMax M1?
MiniMax M1 is the stronger model overall, scoring 40.3 to 27.9 on the Noometry Index. GPT-4.1 nano costs 5.5× less per token, which makes it the better buy when MiniMax M1's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or MiniMax M1?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; MiniMax M1 lists at $0.55 and $2.20.
Is GPT-4.1 nano or MiniMax M1 better for coding?
MiniMax M1 scores higher on coding benchmarks: 39.9 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 GPT-4.1 nano and MiniMax M1 share?
15 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and MiniMax M1 has 18.