Mistral Small 3.1 24B vs MiniMax-M2.7
MiniMax-M2.7 comes out ahead, 61 to 55 on our weighted score, though Mistral Small 3.1 24B is 47% cheaper per token.
Mistral AIMistral Small 3.1 24B
55/100- ECI127.5
- Price$0.229 / $0.436
- Context128K
- Our pick
MiniMaxMiniMax-M2.7
61/100- ECI145.9
- Price$0.30 / $1.20
- Context205K
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MiniMax-M2.7 is our pick
MiniMax-M2.7 is the better all-round choice, scoring 61/100 against Mistral Small 3.1 24B (55). It leads on capability and context window. Mistral Small 3.1 24B wins on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMiniMax-M2.7Capabilities Index (ECI): MiniMax-M2.7 145.9 · Mistral Small 3.1 24B 127.5
- Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · MiniMax-M2.7 $0.525 per 1M tokens (3:1 blend)
- Longest contextMiniMax-M2.7MiniMax-M2.7 204,800 · Mistral Small 3.1 24B 128,000 tokens
- Widest inputsMistral Small 3.1 24BMistral Small 3.1 24B: Text, Images · MiniMax-M2.7: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Small 3.1 24B | MiniMax-M2.7 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 50 | 73 |
| Price | 25% | 76 | 63 |
| Inputs & features | 15% | 60 | 35 |
| Context window | 10% | 24 | 32 |
| Overall | 100% | 55/100 | 61/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral Small 3.1 24BMistral AI | MiniMax-M2.7MiniMax |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 127.5 | 145.9 (best) |
| ECI rank | #132 of 148 | #73 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 47.5% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 5.8% | — |
| Price per million tokens | ||
| Input | $0.229 (best) | $0.30 |
| Output | $0.436 (best) | $1.20 |
| Cached input | — | $0.06 |
| Blended (3:1) | $0.281 (best) | $0.525 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 2 providers | Official MiniMax (minimax.io) API |
| Limits | ||
| Context window | 128,000 tokens | 204,800 tokens (best) |
| Max output | 16,384 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | — | MiniMax-M2.7 |
| API providers | 2 | 29 (best) |
| Released | Mar 17, 2025 | Mar 18, 2026 |
| Knowledge cutoff | Jun 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mistral Small 3.1 24B$3.16
- MiniMax-M2.7$5.40
Which should you choose?
Which is better: Mistral Small 3.1 24B or MiniMax-M2.7?
MiniMax-M2.7 is the better all-round choice, scoring 61/100 against Mistral Small 3.1 24B (55). It leads on capability and context window. Mistral Small 3.1 24B wins on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Small 3.1 24B or MiniMax-M2.7?
Mistral Small 3.1 24B is cheaper at $0.229 input / $0.436 output per million tokens (median across 2 API providers). MiniMax-M2.7 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). At a typical mix of three input tokens to one output token, that is $0.281 per million tokens for Mistral Small 3.1 24B versus $0.525 for MiniMax-M2.7 (1.9× as much).
Which scores higher on benchmarks?
MiniMax-M2.7 scores higher on the Capabilities Index (ECI): MiniMax-M2.7 145.9 (#73 of 148) and Mistral Small 3.1 24B 127.5 (#132 of 148). Their confidence ranges do not overlap (138.2–148.0 vs 122.6–129.4), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Small 3.1 24B and MiniMax-M2.7 yet, so there is no like-for-like coding score. On overall capability, MiniMax-M2.7 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
MiniMax-M2.7 has the largest context window at 204,800 tokens, against 128,000 for Mistral Small 3.1 24B. Maximum output per response: Mistral Small 3.1 24B up to 16,384, MiniMax-M2.7 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Mistral Small 3.1 24B accepts text and images; MiniMax-M2.7 accepts text. Mistral Small 3.1 24B handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
MiniMax-M2.7 is the newest, released Mar 18, 2026. Mistral Small 3.1 24B came out Mar 17, 2025. Knowledge cutoff: Mistral Small 3.1 24B Jun 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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