Model comparison
GPT-5.2 Codex vs MiniMax-M3
MiniMax-M3 is the stronger model overall, scoring 43.5 to 42.2 on the Noometry Index.
Last verified . 2 shared benchmarks.
MiniMaxSummary
- They share 2 benchmarks with published results for both. GPT-5.2 Codex scores higher in 2 categories and MiniMax-M3 in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5.2 Codex leads 40.7 to 22.5.
- MiniMax-M3 is cheaper at $0.30 / $1.20 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
- MiniMax-M3 accepts more context: 1M tokens versus 400K.
- MiniMax-M3 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.2 Codex | MiniMax-M3 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Noometry Index | 42.2 | 43.5 |
| Released | 2025-12-18 | 2026-06-01 |
| Weights | Proprietary | Open |
| Context window | 400K | 1M |
| Max output | 128K | 512K |
| Input $ / M tokens | $1.75 | $0.30 |
| Output $ / M tokens | $14 | $1.20 |
| Results tracked | 5 | 41 |
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Category by category
Coding GPT-5.2 Codex leads
GPT-5.2 Codex: 45.4 (#66), MiniMax-M3: 41.5 (#111)
| Benchmark | GPT-5.2 Codex | MiniMax-M3 |
|---|---|---|
| LMArena WebDev | 1339 | 1482 |
| ALE-Bench | 1,300 | 640.02 |
| FrontierCode | — | 14.7% |
| SWE-bench Verified (bash only) | 72.8% | — |
| SWE-bench Multilingual | 66.3% | — |
| SciCode | — | 47.1% |
| LMArena Coding | — | 1470 |
Agentic & Tool Use GPT-5.2 Codex leads
GPT-5.2 Codex: 40.7 (#20), MiniMax-M3: 22.5 (#121)
| Benchmark | GPT-5.2 Codex | MiniMax-M3 |
|---|---|---|
| Terminal-Bench | 66.5% | — |
| APEX-Agents | — | 37.7% |
| OSWorld 2.0 | — | 4.6% |
| GBAEval | — | 0.9% |
| Vending-Bench 2 | — | 2,158 |
Reasoning Not comparable
GPT-5.2 Codex: —, MiniMax-M3: 29.3 (#83)
| Benchmark | GPT-5.2 Codex | MiniMax-M3 |
|---|---|---|
| SimpleBench | — | 45.8% |
| NYT Connections (extended) | — | 65.1% |
| CritPt | — | 3.7% |
| Chess Puzzles | — | 14% |
| LMArena Hard Prompts | — | 1447 |
| Mystery Game Puzzles | — | 8% |
| DTBench | — | 78.9% |
| LMCA | — | 33.7% |
| Surface Evolver Bench | — | 55% |
| Epoch Capabilities Index | — | 147 |
| ForecastBench | — | 61.4 |
Math Not comparable
GPT-5.2 Codex: —, MiniMax-M3: 39.1 (#83)
| Benchmark | GPT-5.2 Codex | MiniMax-M3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 71.1% |
| ProofBench | — | 18% |
| LMArena Math | — | 1432 |
Knowledge Not comparable
GPT-5.2 Codex: —, MiniMax-M3: 58.4 (#32)
| Benchmark | GPT-5.2 Codex | MiniMax-M3 |
|---|---|---|
| GPQA Diamond | — | 90.9% |
| LMArena Expert | — | 1462 |
Multimodal Not comparable
GPT-5.2 Codex: —, MiniMax-M3: 39.5 (#45)
| Benchmark | GPT-5.2 Codex | MiniMax-M3 |
|---|---|---|
| LMArena Vision | — | 1254 |
| LMArena Document | — | 1435 |
Multilingual Not comparable
GPT-5.2 Codex: —, MiniMax-M3: 53.2 (#70)
| Benchmark | GPT-5.2 Codex | MiniMax-M3 |
|---|---|---|
| LMArena Non-English | — | 1420 |
| LMArena Chinese | — | 1465 |
| LMArena French | — | 1445 |
| LMArena German | — | 1424 |
| LMArena Japanese | — | 1381 |
| LMArena Korean | — | 1372 |
| LMArena Russian | — | 1430 |
| LMArena Spanish | — | 1431 |
Instruction Following Not comparable
GPT-5.2 Codex: —, MiniMax-M3: 75.7 (#56)
| Benchmark | GPT-5.2 Codex | MiniMax-M3 |
|---|---|---|
| LMArena Instruction Following | — | 1433 |
Long Context Not comparable
GPT-5.2 Codex: —, MiniMax-M3: 44.2 (#68)
| Benchmark | GPT-5.2 Codex | MiniMax-M3 |
|---|---|---|
| LMArena Longer Query | — | 1445 |
Writing & Preference Not comparable
GPT-5.2 Codex: —, MiniMax-M3: 62.3 (#79)
| Benchmark | GPT-5.2 Codex | MiniMax-M3 |
|---|---|---|
| LMArena Text | — | 1433 |
| LMArena Creative Writing | — | 1405 |
| EQ-Bench 4 | — | 1150 |
| LMArena Multi-Turn | — | 1441 |
Frequently asked questions
Is GPT-5.2 Codex better than MiniMax-M3?
MiniMax-M3 is the stronger model overall, scoring 43.5 to 42.2 on the Noometry Index.
Which is cheaper, GPT-5.2 Codex or MiniMax-M3?
MiniMax-M3 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.
Is GPT-5.2 Codex or MiniMax-M3 better for coding?
GPT-5.2 Codex scores higher on coding benchmarks: 45.4 versus 41.5 in the Noometry coding category.
Which has the bigger context window?
MiniMax-M3 does, with 1M tokens against 400K.
How many benchmarks do GPT-5.2 Codex and MiniMax-M3 share?
2 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and MiniMax-M3 has 41.