Model comparison
GPT-5.1 vs MiniMax-M2.7
GPT-5.1 is the stronger model overall, scoring 49.0 to 37.7 on the Noometry Index. MiniMax-M2.7 costs 6.5× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Last verified . 25 shared benchmarks.
MiniMaxSummary
- They share 25 benchmarks with published results for both. GPT-5.1 scores higher in 9 categories and MiniMax-M2.7 in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.1 leads 52.2 to 25.9.
- The biggest single-benchmark swing is WeirdML: 60.8% for GPT-5.1 and 37% for MiniMax-M2.7.
- MiniMax-M2.7 is cheaper at $0.30 / $1.20 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- GPT-5.1 accepts more context: 400K tokens versus 205K.
- MiniMax-M2.7 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.1 | MiniMax-M2.7 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Noometry Index | 49.0 | 37.7 |
| Released | 2025-11-13 | 2026-03-18 |
| Weights | Proprietary | Open |
| Context window | 400K | 205K |
| Max output | 128K | 131K |
| Input $ / M tokens | $1.25 | $0.30 |
| Output $ / M tokens | $10 | $1.20 |
| Results tracked | 63 | 30 |
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Category by category
Coding GPT-5.1 leads
GPT-5.1: 46.4 (#66), MiniMax-M2.7: 41.8 (#120)
| Benchmark | GPT-5.1 | MiniMax-M2.7 |
|---|---|---|
| LMArena WebDev | 1395 | 1398 |
| SciCode | 43.3% | 47% |
| WeirdML | 60.8% | 37% |
| LMArena Coding | 1454 | 1454 |
| ALE-Bench | 1,192 | 599.25 |
| SWE-bench Verified | 68% | — |
| SWE-bench Verified (bash only) | 66% | — |
| GSO | 13.7% | — |
| LiveBench Coding | 72.5% | — |
Agentic & Tool Use GPT-5.1 leads
GPT-5.1: 32.7 (#60), MiniMax-M2.7: 25.1 (#111)
| Benchmark | GPT-5.1 | MiniMax-M2.7 |
|---|---|---|
| Terminal-Bench | 47.6% | 45.1% |
| DeepResearch Bench | 42.8% | — |
| ExploitBench | — | 13.3% |
| GBAEval | — | 0% |
| LMArena Search | 1199 | — |
| Vending-Bench 2 | 1,473 | — |
Reasoning GPT-5.1 leads
GPT-5.1: 39.8 (#58), MiniMax-M2.7: 19.7 (#253)
| Benchmark | GPT-5.1 | MiniMax-M2.7 |
|---|---|---|
| CritPt | 4.9% | 0.6% |
| LMArena Hard Prompts | 1457 | 1422 |
| Epoch Capabilities Index | 149.64 | 145.85 |
| ARC-AGI-2 | 17.6% | — |
| SimpleBench | 53.2% | — |
| NYT Connections (extended) | — | 24.7% |
| ARC-AGI-1 | 72.8% | — |
| Chess Puzzles | 32% | — |
| EnigmaEval | 11.2% | — |
| Thematic Generalization | — | 39.3% |
| LiveBench Reasoning | 95.8% | — |
| Mystery Game Puzzles | 19% | — |
| DTBench | 90.1% | — |
| LiveBench Data Analysis | 72.1% | — |
| LMCA | 43.9% | — |
| ForecastBench | 58.1 | — |
| LiveBench | 78.8% | — |
Math GPT-5.1 leads
GPT-5.1: 52.2 (#51), MiniMax-M2.7: 25.9 (#263)
| Benchmark | GPT-5.1 | MiniMax-M2.7 |
|---|---|---|
| LMArena Math | 1447 | 1420 |
| OTIS Mock AIME 2024-2025 | 88.6% | — |
| ProofBench | — | 3% |
| Omni-MATH | 46.4% | — |
| LiveBench Math | 94.5% | — |
| FrontierMath (Feb 2025 set) | 31% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge GPT-5.1 leads
GPT-5.1: 50.6 (#71), MiniMax-M2.7: 37.7 (#152)
| Benchmark | GPT-5.1 | MiniMax-M2.7 |
|---|---|---|
| Vectara Hallucination Rate | 10.9% | 12.9% |
| LMArena Expert | 1470 | 1444 |
| GPQA Diamond | 87.6% | — |
| Humanity's Last Exam | 23.7% | — |
| SimpleQA Verified | 48% | — |
| MMLU-Pro | 57.9% | — |
| GPQA (HELM) | 44.2% | — |
Multimodal Not comparable
GPT-5.1: 44.8 (#19), MiniMax-M2.7: —
| Benchmark | GPT-5.1 | MiniMax-M2.7 |
|---|---|---|
| LMArena Vision | 1250 | — |
| VPCT | 58.7% | — |
| LMArena Document | 1403 | — |
Multilingual GPT-5.1 leads
GPT-5.1: 53.8 (#56), MiniMax-M2.7: 50.3 (#123)
| Benchmark | GPT-5.1 | MiniMax-M2.7 |
|---|---|---|
| LMArena Non-English | 1431 | 1382 |
| LMArena Chinese | 1495 | 1441 |
| LMArena French | 1450 | 1421 |
| LMArena German | 1438 | 1398 |
| LMArena Japanese | 1453 | 1262 |
| LMArena Korean | 1401 | 1313 |
| LMArena Russian | 1435 | 1383 |
| LMArena Spanish | 1433 | 1403 |
Instruction Following GPT-5.1 leads
GPT-5.1: 83.9 (#1), MiniMax-M2.7: 74.1 (#103)
| Benchmark | GPT-5.1 | MiniMax-M2.7 |
|---|---|---|
| LMArena Instruction Following | 1443 | 1405 |
| LiveBench Instruction Following | 93.3% | — |
| IFEval | 93.5% | — |
Long Context GPT-5.1 leads
GPT-5.1: 47.6 (#14), MiniMax-M2.7: 43.3 (#99)
| Benchmark | GPT-5.1 | MiniMax-M2.7 |
|---|---|---|
| LMArena Longer Query | 1447 | 1419 |
| CL-bench | 23.7% | — |
| CL-bench Life | 17.3% | — |
Writing & Preference GPT-5.1 leads
GPT-5.1: 64.5 (#55), MiniMax-M2.7: 58.9 (#112)
| Benchmark | GPT-5.1 | MiniMax-M2.7 |
|---|---|---|
| LMArena Text | 1443 | 1405 |
| LMArena Creative Writing | 1427 | 1354 |
| LMArena Multi-Turn | 1450 | 1412 |
| WildBench | 86.3% | — |
| LiveBench Language | 80.2% | — |
Frequently asked questions
Is GPT-5.1 better than MiniMax-M2.7?
GPT-5.1 is the stronger model overall, scoring 49.0 to 37.7 on the Noometry Index. MiniMax-M2.7 costs 6.5× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Which is cheaper, GPT-5.1 or MiniMax-M2.7?
MiniMax-M2.7 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GPT-5.1 or MiniMax-M2.7 better for coding?
GPT-5.1 scores higher on coding benchmarks: 46.4 versus 41.8 in the Noometry coding category.
Which has the bigger context window?
GPT-5.1 does, with 400K tokens against 205K.
How many benchmarks do GPT-5.1 and MiniMax-M2.7 share?
25 benchmarks have published results for both models. GPT-5.1 has 63 scored results on Noometry and MiniMax-M2.7 has 30.