Model comparison
GPT-5.4 mini vs MiniMax-M2.7
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 37.7 on the Noometry Index. MiniMax-M2.7 costs 3.2× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. GPT-5.4 mini scores higher in 8 categories and MiniMax-M2.7 in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.4 mini leads 45.5 to 25.9.
- The biggest single-benchmark swing is NYT Connections (extended): 61.8% for GPT-5.4 mini and 24.7% for MiniMax-M2.7.
- MiniMax-M2.7 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.75 / $4.50 for GPT-5.4 mini.
- GPT-5.4 mini accepts more context: 400K tokens versus 205K.
- MiniMax-M2.7 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 mini | MiniMax-M2.7 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Noometry Index | 45.0 | 37.7 |
| Released | 2026-03-17 | 2026-03-18 |
| Weights | Proprietary | Open |
| Context window | 400K | 205K |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.75 | $0.30 |
| Output $ / M tokens | $4.50 | $1.20 |
| Results tracked | 46 | 30 |
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Category by category
Coding GPT-5.4 mini leads
GPT-5.4 mini: 45.2 (#72), MiniMax-M2.7: 41.8 (#120)
| Benchmark | GPT-5.4 mini | MiniMax-M2.7 |
|---|---|---|
| LMArena WebDev | 1397 | 1398 |
| SciCode | 49.9% | 47% |
| WeirdML | 60.3% | 37% |
| LMArena Coding | 1438 | 1454 |
| ALE-Bench | 1,189 | 599.25 |
| FrontierCode | 27% | — |
Agentic & Tool Use GPT-5.4 mini leads
GPT-5.4 mini: 29.9 (#81), MiniMax-M2.7: 25.1 (#111)
| Benchmark | GPT-5.4 mini | MiniMax-M2.7 |
|---|---|---|
| Terminal-Bench | — | 45.1% |
| DeepResearch Bench | 36.3% | — |
| ExploitBench | — | 13.3% |
| GBAEval | — | 0% |
Reasoning GPT-5.4 mini leads
GPT-5.4 mini: 30.4 (#85), MiniMax-M2.7: 19.7 (#253)
| Benchmark | GPT-5.4 mini | MiniMax-M2.7 |
|---|---|---|
| NYT Connections (extended) | 61.8% | 24.7% |
| CritPt | 10% | 0.6% |
| Thematic Generalization | 61.7% | 39.3% |
| LMArena Hard Prompts | 1424 | 1422 |
| Epoch Capabilities Index | 148.84 | 145.85 |
| ARC-AGI-2 | 18.9% | — |
| Kagi LLM Benchmark | 37.9% | — |
| ARC-AGI-1 | 63.7% | — |
| Chess Puzzles | 24% | — |
| Mystery Game Puzzles | 11% | — |
| DTBench | 80% | — |
| LMCA | 40.8% | — |
| ForecastBench | 57 | — |
Math GPT-5.4 mini leads
GPT-5.4 mini: 45.5 (#75), MiniMax-M2.7: 25.9 (#263)
| Benchmark | GPT-5.4 mini | MiniMax-M2.7 |
|---|---|---|
| ProofBench | 21% | 3% |
| LMArena Math | 1419 | 1420 |
| FrontierMath (Tiers 1-3) | 51.2% | — |
| FrontierMath Tier 4 | 9.8% | — |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| FrontierMath (Feb 2025 set) | 28.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GPT-5.4 mini leads
GPT-5.4 mini: 51.5 (#67), MiniMax-M2.7: 37.7 (#152)
| Benchmark | GPT-5.4 mini | MiniMax-M2.7 |
|---|---|---|
| Vectara Hallucination Rate | 5.5% | 12.9% |
| LMArena Expert | 1435 | 1444 |
| GPQA Diamond | 86.9% | — |
| SimpleQA Verified | 29.4% | — |
Multimodal Not comparable
GPT-5.4 mini: 39.7 (#56), MiniMax-M2.7: —
| Benchmark | GPT-5.4 mini | MiniMax-M2.7 |
|---|---|---|
| LMArena Vision | 1245 | — |
Multilingual GPT-5.4 mini leads
GPT-5.4 mini: 51.9 (#96), MiniMax-M2.7: 50.3 (#123)
| Benchmark | GPT-5.4 mini | MiniMax-M2.7 |
|---|---|---|
| LMArena Non-English | 1405 | 1382 |
| LMArena Chinese | 1446 | 1441 |
| LMArena French | 1440 | 1421 |
| LMArena German | 1409 | 1398 |
| LMArena Japanese | 1374 | 1262 |
| LMArena Korean | 1368 | 1313 |
| LMArena Russian | 1417 | 1383 |
| LMArena Spanish | 1405 | 1403 |
Instruction Following Too close to call
GPT-5.4 mini: 74.1 (#102), MiniMax-M2.7: 74.1 (#103)
| Benchmark | GPT-5.4 mini | MiniMax-M2.7 |
|---|---|---|
| LMArena Instruction Following | 1405 | 1405 |
Long Context Too close to call
GPT-5.4 mini: 43.0 (#112), MiniMax-M2.7: 43.3 (#99)
| Benchmark | GPT-5.4 mini | MiniMax-M2.7 |
|---|---|---|
| LMArena Longer Query | 1407 | 1419 |
Writing & Preference GPT-5.4 mini leads
GPT-5.4 mini: 64.0 (#58), MiniMax-M2.7: 58.9 (#112)
| Benchmark | GPT-5.4 mini | MiniMax-M2.7 |
|---|---|---|
| LMArena Text | 1412 | 1405 |
| LMArena Creative Writing | 1370 | 1354 |
| LMArena Multi-Turn | 1429 | 1412 |
| EQ-Bench Creative Writing | 1665 | — |
Frequently asked questions
Is GPT-5.4 mini better than MiniMax-M2.7?
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 37.7 on the Noometry Index. MiniMax-M2.7 costs 3.2× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Which is cheaper, GPT-5.4 mini 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-5.4 mini lists at $0.75 and $4.50.
Is GPT-5.4 mini or MiniMax-M2.7 better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.2 versus 41.8 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 mini does, with 400K tokens against 205K.
How many benchmarks do GPT-5.4 mini and MiniMax-M2.7 share?
27 benchmarks have published results for both models. GPT-5.4 mini has 46 scored results on Noometry and MiniMax-M2.7 has 30.