Model comparison
GPT-5.5 Pro vs MiniMax-M2.1
GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 38.9 on the Noometry Index. MiniMax-M2.1 costs 129× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
MiniMaxSummary
- The widest gap is in reasoning, where GPT-5.5 Pro leads 73.3 to 16.6.
- MiniMax-M2.1 is cheaper at $0.30 / $1.20 per million input/output tokens, against $30 / $180 for GPT-5.5 Pro.
- GPT-5.5 Pro accepts more context: 1.05M tokens versus 205K.
- MiniMax-M2.1 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.5 Pro | MiniMax-M2.1 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Noometry Index | 64.3 | 38.9 |
| Released | 2026-04-23 | 2025-12-23 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 205K |
| Max output | 128K | 131K |
| Input $ / M tokens | $30 | $0.30 |
| Output $ / M tokens | $180 | $1.20 |
| Results tracked | 14 | 22 |
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Category by category
Coding Not comparable
GPT-5.5 Pro: —, MiniMax-M2.1: 40.4 (#143)
| Benchmark | GPT-5.5 Pro | MiniMax-M2.1 |
|---|---|---|
| LMArena WebDev | — | 1384 |
| LMArena Coding | — | 1421 |
| ALE-Bench | — | 623.83 |
Agentic & Tool Use Not comparable
GPT-5.5 Pro: —, MiniMax-M2.1: 27.9 (#98)
| Benchmark | GPT-5.5 Pro | MiniMax-M2.1 |
|---|---|---|
| Terminal-Bench | — | 36.6% |
Reasoning GPT-5.5 Pro leads
GPT-5.5 Pro: 73.3 (#10), MiniMax-M2.1: 16.6 (#302)
| Benchmark | GPT-5.5 Pro | MiniMax-M2.1 |
|---|---|---|
| ARC-AGI-2 | 84.6% | — |
| SimpleBench | 76.9% | — |
| NYT Connections (extended) | — | 11.2% |
| ARC-AGI-1 | 96.5% | — |
| CritPt | 30.6% | — |
| Chess Puzzles | 64% | — |
| LMArena Hard Prompts | — | 1411 |
| DTBench | 96% | — |
| LMCA | 53.9% | — |
| Epoch Capabilities Index | 162.07 | — |
Math GPT-5.5 Pro leads
GPT-5.5 Pro: 84.0 (#10), MiniMax-M2.1: 38.3 (#138)
| Benchmark | GPT-5.5 Pro | MiniMax-M2.1 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 87.7% | — |
| FrontierMath Tier 4 | 78% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| LMArena Math | — | 1397 |
| FrontierMath (Feb 2025 set) | 52.4% | — |
| FrontierMath Tier 4 (v1) | 39.6% | — |
Knowledge GPT-5.5 Pro leads
GPT-5.5 Pro: 64.1 (#19), MiniMax-M2.1: 38.3 (#147)
| Benchmark | GPT-5.5 Pro | MiniMax-M2.1 |
|---|---|---|
| GPQA Diamond | 93.9% | — |
| Vectara Hallucination Rate | — | 11.8% |
| LMArena Expert | — | 1431 |
Multilingual Not comparable
GPT-5.5 Pro: —, MiniMax-M2.1: 50.0 (#128)
| Benchmark | GPT-5.5 Pro | MiniMax-M2.1 |
|---|---|---|
| LMArena Non-English | — | 1378 |
| LMArena Chinese | — | 1430 |
| LMArena French | — | 1404 |
| LMArena German | — | 1381 |
| LMArena Japanese | — | 1287 |
| LMArena Korean | — | 1298 |
| LMArena Russian | — | 1387 |
| LMArena Spanish | — | 1397 |
Instruction Following Not comparable
GPT-5.5 Pro: —, MiniMax-M2.1: 73.8 (#112)
| Benchmark | GPT-5.5 Pro | MiniMax-M2.1 |
|---|---|---|
| LMArena Instruction Following | — | 1400 |
Long Context Not comparable
GPT-5.5 Pro: —, MiniMax-M2.1: 43.2 (#101)
| Benchmark | GPT-5.5 Pro | MiniMax-M2.1 |
|---|---|---|
| LMArena Longer Query | — | 1416 |
Writing & Preference Not comparable
GPT-5.5 Pro: —, MiniMax-M2.1: 58.3 (#120)
| Benchmark | GPT-5.5 Pro | MiniMax-M2.1 |
|---|---|---|
| LMArena Text | — | 1392 |
| LMArena Creative Writing | — | 1361 |
| LMArena Multi-Turn | — | 1396 |
Frequently asked questions
Is GPT-5.5 Pro better than MiniMax-M2.1?
GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 38.9 on the Noometry Index. MiniMax-M2.1 costs 129× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5.5 Pro or MiniMax-M2.1?
MiniMax-M2.1 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GPT-5.5 Pro lists at $30 and $180.
Which has the bigger context window?
GPT-5.5 Pro does, with 1.05M tokens against 205K.
How many benchmarks do GPT-5.5 Pro and MiniMax-M2.1 share?
0 benchmarks have published results for both models. GPT-5.5 Pro has 14 scored results on Noometry and MiniMax-M2.1 has 22.