Model comparison
GPT-5-Codex vs MiniMax-M2.1
MiniMax-M2.1 is the stronger model overall, scoring 38.9 to 37.9 on the Noometry Index.
Last verified . 1 shared benchmarks.
MiniMaxSummary
- They share 1 benchmark with published results for both. GPT-5-Codex scores higher in 3 categories and MiniMax-M2.1 in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5-Codex leads 30.9 to 16.6.
- The biggest single-benchmark swing is Terminal-Bench: 44.3% for GPT-5-Codex and 36.6% for MiniMax-M2.1.
- MiniMax-M2.1 is cheaper at $0.30 / $1.20 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
- GPT-5-Codex accepts more context: 400K tokens versus 205K.
- MiniMax-M2.1 has downloadable open weights; the other is API-only.
Side by side
| GPT-5-Codex | MiniMax-M2.1 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Noometry Index | 37.9 | 38.9 |
| Released | 2025-09-15 | 2025-12-23 |
| 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 | 3 | 22 |
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Category by category
Coding GPT-5-Codex leads
GPT-5-Codex: 42.4 (#103), MiniMax-M2.1: 40.4 (#143)
| Benchmark | GPT-5-Codex | MiniMax-M2.1 |
|---|---|---|
| LMArena WebDev | — | 1384 |
| WeirdML | 54.5% | — |
| LMArena Coding | — | 1421 |
| ALE-Bench | — | 623.83 |
Agentic & Tool Use GPT-5-Codex leads
GPT-5-Codex: 31.0 (#72), MiniMax-M2.1: 27.9 (#98)
| Benchmark | GPT-5-Codex | MiniMax-M2.1 |
|---|---|---|
| Terminal-Bench | 44.3% | 36.6% |
Reasoning GPT-5-Codex leads
GPT-5-Codex: 30.9 (#83), MiniMax-M2.1: 16.6 (#302)
| Benchmark | GPT-5-Codex | MiniMax-M2.1 |
|---|---|---|
| Kagi LLM Benchmark | 70.3% | — |
| NYT Connections (extended) | — | 11.2% |
| LMArena Hard Prompts | — | 1411 |
Math Not comparable
GPT-5-Codex: —, MiniMax-M2.1: 38.3 (#138)
| Benchmark | GPT-5-Codex | MiniMax-M2.1 |
|---|---|---|
| LMArena Math | — | 1397 |
Knowledge Not comparable
GPT-5-Codex: —, MiniMax-M2.1: 38.3 (#147)
| Benchmark | GPT-5-Codex | MiniMax-M2.1 |
|---|---|---|
| Vectara Hallucination Rate | — | 11.8% |
| LMArena Expert | — | 1431 |
Multilingual Not comparable
GPT-5-Codex: —, MiniMax-M2.1: 50.0 (#128)
| Benchmark | GPT-5-Codex | 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-Codex: —, MiniMax-M2.1: 73.8 (#112)
| Benchmark | GPT-5-Codex | MiniMax-M2.1 |
|---|---|---|
| LMArena Instruction Following | — | 1400 |
Long Context Not comparable
GPT-5-Codex: —, MiniMax-M2.1: 43.2 (#101)
| Benchmark | GPT-5-Codex | MiniMax-M2.1 |
|---|---|---|
| LMArena Longer Query | — | 1416 |
Writing & Preference Not comparable
GPT-5-Codex: —, MiniMax-M2.1: 58.3 (#120)
| Benchmark | GPT-5-Codex | MiniMax-M2.1 |
|---|---|---|
| LMArena Text | — | 1392 |
| LMArena Creative Writing | — | 1361 |
| LMArena Multi-Turn | — | 1396 |
Frequently asked questions
Is GPT-5-Codex better than MiniMax-M2.1?
MiniMax-M2.1 is the stronger model overall, scoring 38.9 to 37.9 on the Noometry Index.
Which is cheaper, GPT-5-Codex 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-Codex lists at $1.25 and $10.
Is GPT-5-Codex or MiniMax-M2.1 better for coding?
GPT-5-Codex scores higher on coding benchmarks: 42.4 versus 40.4 in the Noometry coding category.
Which has the bigger context window?
GPT-5-Codex does, with 400K tokens against 205K.
How many benchmarks do GPT-5-Codex and MiniMax-M2.1 share?
1 benchmark has published results for both models. GPT-5-Codex has 3 scored results on Noometry and MiniMax-M2.1 has 22.