Model comparison
GPT-4.1 vs MiniMax M1
MiniMax M1 is the stronger model overall, scoring 40.3 to 35.9 on the Noometry Index.
Last verified . 18 shared benchmarks.
MiniMaxSummary
- They share 18 benchmarks with published results for both. GPT-4.1 scores higher in 4 categories and MiniMax M1 in 4 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where MiniMax M1 leads 37.5 to 22.3.
- The biggest single-benchmark swing is Fiction.LiveBench: 63.9% for GPT-4.1 and 69.4% for MiniMax M1.
- MiniMax M1 is cheaper at $0.55 / $2.20 per million input/output tokens, against $2 / $8 for GPT-4.1.
- GPT-4.1 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 | MiniMax M1 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Noometry Index | 35.9 | 40.3 |
| Released | 2025-04-14 | 2025-06-13 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 1M |
| Max output | 33K | 40K |
| Input $ / M tokens | $2 | $0.55 |
| Output $ / M tokens | $8 | $2.20 |
| Results tracked | 52 | 18 |
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Category by category
Coding MiniMax M1 leads
GPT-4.1: 34.4 (#238), MiniMax M1: 39.9 (#153)
| Benchmark | GPT-4.1 | MiniMax M1 |
|---|---|---|
| LMArena Coding | 1391 | 1359 |
| SWE-bench Verified | 48.5% | — |
| SWE-bench Verified (bash only) | 39.6% | — |
| Aider Polyglot | 52.4% | — |
| WeirdML | 39% | — |
| CadEval | 42% | — |
| ALE-Bench | 558.1 | — |
Agentic & Tool Use Not comparable
GPT-4.1: 34.7 (#43), MiniMax M1: —
| Benchmark | GPT-4.1 | MiniMax M1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 54% | — |
Reasoning MiniMax M1 leads
GPT-4.1: 11.7 (#339), MiniMax M1: 26.9 (#126)
| Benchmark | GPT-4.1 | MiniMax M1 |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1339 |
| ARC-AGI-2 | 0.4% | — |
| SimpleBench | 27% | — |
| Kagi LLM Benchmark | 52.3% | — |
| ARC-AGI-1 | 5.5% | — |
| Chess Puzzles | 6% | — |
| EnigmaEval | 2.2% | — |
| DTBench | 68.3% | — |
| LMCA | 25.6% | — |
| Epoch Capabilities Index | 136.78 | — |
| ForecastBench | 61.5 | — |
Math MiniMax M1 leads
GPT-4.1: 22.3 (#280), MiniMax M1: 37.5 (#151)
| Benchmark | GPT-4.1 | MiniMax M1 |
|---|---|---|
| LMArena Math | 1370 | 1361 |
| FrontierMath (Tiers 1-3) | 6% | — |
| OTIS Mock AIME 2024-2025 | 38.3% | — |
| Omni-MATH | 47.1% | — |
| MATH Level 5 | 83% | — |
| FrontierMath (Feb 2025 set) | 5.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Too close to call
GPT-4.1: 37.1 (#160), MiniMax M1: 36.4 (#170)
| Benchmark | GPT-4.1 | MiniMax M1 |
|---|---|---|
| LMArena Expert | 1364 | 1317 |
| GPQA Diamond | 66.9% | — |
| Humanity's Last Exam | 5.4% | — |
| SimpleQA Verified | 31.1% | — |
| MMLU-Pro | 81.1% | — |
| Vectara Hallucination Rate | 5.6% | — |
| GPQA (HELM) | 65.9% | — |
Multimodal Not comparable
GPT-4.1: 38.2 (#67), MiniMax M1: —
| Benchmark | GPT-4.1 | MiniMax M1 |
|---|---|---|
| LMArena Vision | 1211 | — |
| GeoBench | 72% | — |
Multilingual GPT-4.1 leads
GPT-4.1: 49.4 (#133), MiniMax M1: 45.8 (#163)
| Benchmark | GPT-4.1 | MiniMax M1 |
|---|---|---|
| LMArena Non-English | 1370 | 1319 |
| LMArena Chinese | 1382 | 1360 |
| LMArena French | 1382 | 1370 |
| LMArena German | 1381 | 1350 |
| LMArena Japanese | 1319 | 1217 |
| LMArena Korean | 1339 | 1266 |
| LMArena Russian | 1377 | 1329 |
| LMArena Spanish | 1376 | 1353 |
Instruction Following GPT-4.1 leads
GPT-4.1: 71.3 (#153), MiniMax M1: 69.3 (#174)
| Benchmark | GPT-4.1 | MiniMax M1 |
|---|---|---|
| LMArena Instruction Following | 1367 | 1312 |
| IFEval | 83.8% | — |
Long Context MiniMax M1 leads
GPT-4.1: 40.0 (#163), MiniMax M1: 41.4 (#141)
| Benchmark | GPT-4.1 | MiniMax M1 |
|---|---|---|
| Fiction.LiveBench | 63.9% | 69.4% |
| LMArena Longer Query | 1385 | 1326 |
Writing & Preference GPT-4.1 leads
GPT-4.1: 57.6 (#125), MiniMax M1: 53.1 (#161)
| Benchmark | GPT-4.1 | MiniMax M1 |
|---|---|---|
| LMArena Text | 1383 | 1343 |
| LMArena Creative Writing | 1363 | 1298 |
| LMArena Multi-Turn | 1398 | 1335 |
| EQ-Bench Creative Writing | 1420 | — |
| WildBench | 85.4% | — |
Frequently asked questions
Is GPT-4.1 better than MiniMax M1?
MiniMax M1 is the stronger model overall, scoring 40.3 to 35.9 on the Noometry Index.
Which is cheaper, GPT-4.1 or MiniMax M1?
MiniMax M1 is cheaper. It lists at $0.55 per million input tokens and $2.20 per million output tokens; GPT-4.1 lists at $2 and $8.
Is GPT-4.1 or MiniMax M1 better for coding?
MiniMax M1 scores higher on coding benchmarks: 39.9 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 does, with 1.05M tokens against 1M.
How many benchmarks do GPT-4.1 and MiniMax M1 share?
18 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and MiniMax M1 has 18.