Model comparison
GPT-4o mini vs MiniMax M1
MiniMax M1 is the stronger model overall, scoring 40.3 to 25.5 on the Noometry Index. GPT-4o mini costs 3.7× less per token, which makes it the better buy when MiniMax M1's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
MiniMaxSummary
- They share 17 benchmarks with published results for both. GPT-4o mini scores higher in 0 categories and MiniMax M1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where MiniMax M1 leads 37.5 to 10.4.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.55 / $2.20 for MiniMax M1.
- MiniMax M1 accepts more context: 1M tokens versus 128K.
- MiniMax M1 has downloadable open weights; the other is API-only.
Side by side
| GPT-4o mini | MiniMax M1 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Noometry Index | 25.5 | 40.3 |
| Released | 2024-07-18 | 2025-06-13 |
| Weights | Proprietary | Open |
| Context window | 128K | 1M |
| Max output | 16K | 40K |
| Input $ / M tokens | $0.15 | $0.55 |
| Output $ / M tokens | $0.60 | $2.20 |
| Results tracked | 60 | 18 |
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Category by category
Coding MiniMax M1 leads
GPT-4o mini: 22.0 (#335), MiniMax M1: 39.9 (#153)
| Benchmark | GPT-4o mini | MiniMax M1 |
|---|---|---|
| LMArena Coding | 1290 | 1359 |
| Aider Polyglot | 3.6% | — |
| WeirdML | 11.8% | — |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 43.1% | — |
| BigCodeBench Complete | 57.4% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use Not comparable
GPT-4o mini: 27.5 (#101), MiniMax M1: —
| Benchmark | GPT-4o mini | MiniMax M1 |
|---|---|---|
| BALROG | 17.4% | — |
Reasoning MiniMax M1 leads
GPT-4o mini: 8.7 (#347), MiniMax M1: 26.9 (#126)
| Benchmark | GPT-4o mini | MiniMax M1 |
|---|---|---|
| LMArena Hard Prompts | 1267 | 1339 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 10.7% | — |
| Kagi LLM Benchmark | 28.8% | — |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | 32.8% | — |
| Mystery Game Puzzles | 12% | — |
| DTBench | 54.4% | — |
| LiveBench Data Analysis | 50% | — |
| LMCA | 10.4% | — |
| Epoch Capabilities Index | 126.56 | — |
| LiveBench | 41.3% | — |
| PIQA | 88.7% | — |
Math MiniMax M1 leads
GPT-4o mini: 10.4 (#314), MiniMax M1: 37.5 (#151)
| Benchmark | GPT-4o mini | MiniMax M1 |
|---|---|---|
| LMArena Math | 1267 | 1361 |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| OTIS Mock AIME 2024-2025 | 6.9% | — |
| Omni-MATH | 28% | — |
| LiveBench Math | 36.3% | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |
Knowledge MiniMax M1 leads
GPT-4o mini: 17.7 (#284), MiniMax M1: 36.4 (#170)
| Benchmark | GPT-4o mini | MiniMax M1 |
|---|---|---|
| LMArena Expert | 1235 | 1317 |
| GPQA Diamond | 37.7% | — |
| SimpleQA Verified | 8.3% | — |
| MMLU-Pro | 60.3% | — |
| Confabulations | 37.2% | — |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |
Multimodal Not comparable
GPT-4o mini: 25.9 (#122), MiniMax M1: —
| Benchmark | GPT-4o mini | MiniMax M1 |
|---|---|---|
| LMArena Vision | 1066 | — |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
Multilingual MiniMax M1 leads
GPT-4o mini: 42.0 (#199), MiniMax M1: 45.8 (#163)
| Benchmark | GPT-4o mini | MiniMax M1 |
|---|---|---|
| LMArena Non-English | 1266 | 1319 |
| LMArena Chinese | 1265 | 1360 |
| LMArena French | 1297 | 1370 |
| LMArena German | 1272 | 1350 |
| LMArena Japanese | 1216 | 1217 |
| LMArena Korean | 1195 | 1266 |
| LMArena Russian | 1275 | 1329 |
| LMArena Spanish | 1276 | 1353 |
Instruction Following MiniMax M1 leads
GPT-4o mini: 61.9 (#239), MiniMax M1: 69.3 (#174)
| Benchmark | GPT-4o mini | MiniMax M1 |
|---|---|---|
| LMArena Instruction Following | 1258 | 1312 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
Long Context MiniMax M1 leads
GPT-4o mini: 39.1 (#186), MiniMax M1: 41.4 (#141)
| Benchmark | GPT-4o mini | MiniMax M1 |
|---|---|---|
| LMArena Longer Query | 1289 | 1326 |
| Fiction.LiveBench | — | 69.4% |
Writing & Preference MiniMax M1 leads
GPT-4o mini: 39.5 (#248), MiniMax M1: 53.1 (#161)
| Benchmark | GPT-4o mini | MiniMax M1 |
|---|---|---|
| LMArena Text | 1286 | 1343 |
| LMArena Creative Writing | 1268 | 1298 |
| LMArena Multi-Turn | 1285 | 1335 |
| Short-Story Creative Writing | 67.2% | — |
| EQ-Bench Creative Writing | 873 | — |
| WildBench | 79.1% | — |
| LiveBench Language | 28.6% | — |
Frequently asked questions
Is GPT-4o mini better than MiniMax M1?
MiniMax M1 is the stronger model overall, scoring 40.3 to 25.5 on the Noometry Index. GPT-4o mini costs 3.7× less per token, which makes it the better buy when MiniMax M1's lead doesn't matter for your workload.
Which is cheaper, GPT-4o mini or MiniMax M1?
GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; MiniMax M1 lists at $0.55 and $2.20.
Is GPT-4o mini or MiniMax M1 better for coding?
MiniMax M1 scores higher on coding benchmarks: 39.9 versus 22.0 in the Noometry coding category.
Which has the bigger context window?
MiniMax M1 does, with 1M tokens against 128K.
How many benchmarks do GPT-4o mini and MiniMax M1 share?
17 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and MiniMax M1 has 18.