Model comparison
Devstral Small 2505 vs MiniMax-M3
MiniMax-M3 is the stronger model overall, scoring 43.5 to 33.9 on the Noometry Index. Devstral Small 2505 costs 3.5× less per token, which makes it the better buy when MiniMax-M3's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Mistral AI
MiniMaxSummary
- They share 2 benchmarks with published results for both. Devstral Small 2505 scores higher in 0 categories and MiniMax-M3 in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where MiniMax-M3 leads 29.3 to 19.1.
- The biggest single-benchmark swing is SciCode: 28.8% for Devstral Small 2505 and 47.1% for MiniMax-M3.
- Devstral Small 2505 is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M3.
- MiniMax-M3 accepts more context: 1M tokens versus 128K.
Side by side
| Devstral Small 2505 | MiniMax-M3 | |
|---|---|---|
| Provider | Mistral AI | MiniMax |
| Noometry Index | 33.9 | 43.5 |
| Released | 2025-05-07 | 2026-06-01 |
| Weights | Open | Open |
| Context window | 128K | 1M |
| Max output | 128K | 512K |
| Input $ / M tokens | $0.10 | $0.30 |
| Output $ / M tokens | $0.30 | $1.20 |
| Results tracked | 4 | 41 |
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Category by category
Coding MiniMax-M3 leads
Devstral Small 2505: 38.6 (#160), MiniMax-M3: 41.5 (#111)
| Benchmark | Devstral Small 2505 | MiniMax-M3 |
|---|---|---|
| SciCode | 28.8% | 47.1% |
| FrontierCode | — | 14.7% |
| SWE-bench Verified (bash only) | 56.4% | — |
| LMArena WebDev | — | 1482 |
| LMArena Coding | — | 1470 |
| ALE-Bench | — | 640.02 |
Agentic & Tool Use Not comparable
Devstral Small 2505: —, MiniMax-M3: 22.5 (#121)
| Benchmark | Devstral Small 2505 | MiniMax-M3 |
|---|---|---|
| APEX-Agents | — | 37.7% |
| OSWorld 2.0 | — | 4.6% |
| GBAEval | — | 0.9% |
| Vending-Bench 2 | — | 2,158 |
Reasoning MiniMax-M3 leads
Devstral Small 2505: 19.1 (#243), MiniMax-M3: 29.3 (#83)
| Benchmark | Devstral Small 2505 | MiniMax-M3 |
|---|---|---|
| CritPt | 0% | 3.7% |
| SimpleBench | — | 45.8% |
| Kagi LLM Benchmark | 37.7% | — |
| NYT Connections (extended) | — | 65.1% |
| 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
Devstral Small 2505: —, MiniMax-M3: 39.1 (#83)
| Benchmark | Devstral Small 2505 | MiniMax-M3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 71.1% |
| ProofBench | — | 18% |
| LMArena Math | — | 1432 |
Knowledge Not comparable
Devstral Small 2505: —, MiniMax-M3: 58.4 (#32)
| Benchmark | Devstral Small 2505 | MiniMax-M3 |
|---|---|---|
| GPQA Diamond | — | 90.9% |
| LMArena Expert | — | 1462 |
Multimodal Not comparable
Devstral Small 2505: —, MiniMax-M3: 39.5 (#45)
| Benchmark | Devstral Small 2505 | MiniMax-M3 |
|---|---|---|
| LMArena Vision | — | 1254 |
| LMArena Document | — | 1435 |
Multilingual Not comparable
Devstral Small 2505: —, MiniMax-M3: 53.2 (#70)
| Benchmark | Devstral Small 2505 | 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
Devstral Small 2505: —, MiniMax-M3: 75.7 (#56)
| Benchmark | Devstral Small 2505 | MiniMax-M3 |
|---|---|---|
| LMArena Instruction Following | — | 1433 |
Long Context Not comparable
Devstral Small 2505: —, MiniMax-M3: 44.2 (#68)
| Benchmark | Devstral Small 2505 | MiniMax-M3 |
|---|---|---|
| LMArena Longer Query | — | 1445 |
Writing & Preference Not comparable
Devstral Small 2505: —, MiniMax-M3: 62.3 (#79)
| Benchmark | Devstral Small 2505 | MiniMax-M3 |
|---|---|---|
| LMArena Text | — | 1433 |
| LMArena Creative Writing | — | 1405 |
| EQ-Bench 4 | — | 1150 |
| LMArena Multi-Turn | — | 1441 |
Frequently asked questions
Is Devstral Small 2505 better than MiniMax-M3?
MiniMax-M3 is the stronger model overall, scoring 43.5 to 33.9 on the Noometry Index. Devstral Small 2505 costs 3.5× less per token, which makes it the better buy when MiniMax-M3's lead doesn't matter for your workload.
Which is cheaper, Devstral Small 2505 or MiniMax-M3?
Devstral Small 2505 is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; MiniMax-M3 lists at $0.30 and $1.20.
Is Devstral Small 2505 or MiniMax-M3 better for coding?
MiniMax-M3 scores higher on coding benchmarks: 41.5 versus 38.6 in the Noometry coding category.
Which has the bigger context window?
MiniMax-M3 does, with 1M tokens against 128K.
How many benchmarks do Devstral Small 2505 and MiniMax-M3 share?
2 benchmarks have published results for both models. Devstral Small 2505 has 4 scored results on Noometry and MiniMax-M3 has 41.