Mistral Medium 3.1 vs Voxtral Small 24B 2507
Voxtral Small 24B 2507 comes out ahead, 55 to 50 on our weighted score, and it is the cheaper option too.
Mistral AIMistral Medium 3.1
50/100- ECI—
- Price$0.40 / $2.00
- Context262K
- Our pickMistral AI
Voxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.30
- Context33K
Add a model
Make it a three-way comparison.
Voxtral Small 24B 2507 is our pick
Voxtral Small 24B 2507 is the better all-round choice, scoring 55/100 against Mistral Medium 3.1 (50). It leads on price. Mistral Medium 3.1 wins on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceVoxtral Small 24B 2507Voxtral Small 24B 2507 $0.15 · Mistral Medium 3.1 $0.80 per 1M tokens (3:1 blend)
- Longest contextMistral Medium 3.1Mistral Medium 3.1 262,144 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsSame inputsMistral Medium 3.1: Text, Images · Voxtral Small 24B 2507: Text, Audio
- Self-hostingVoxtral Small 24B 2507Publishes downloadable weights (Apache 2.0)
| Measure | Weight | Mistral Medium 3.1 | Voxtral Small 24B 2507 |
|---|---|---|---|
| Price | 50% | 54 | 89 |
| Inputs & features | 30% | 50 | 35 |
| Context window | 20% | 37 | 0 |
| Overall | 100% | 50/100 | 55/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral Medium 3.1Mistral AI | Voxtral Small 24B 2507Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.40 | $0.10 (best) |
| Output | $2.00 | $0.30 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.80 | $0.15 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Mistral API |
| Limits | ||
| Context window | 262,144 tokens (best) | 32,768 tokens |
| Max output | 262,144 tokens (best) | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | Yes |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | OpenApache 2.0 |
| API model ID | mistral-medium-2508 | voxtral-small-latest |
| API providers | 1 | 7 (best) |
| Released | Aug 12, 2025 | Jul 15, 2025 |
| Knowledge cutoff | May 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mistral Medium 3.1$8.00
- Voxtral Small 24B 2507$1.60
Which should you choose?
Which is better: Mistral Medium 3.1 or Voxtral Small 24B 2507?
Voxtral Small 24B 2507 is the better all-round choice, scoring 55/100 against Mistral Medium 3.1 (50). It leads on price. Mistral Medium 3.1 wins on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Mistral Medium 3.1 or Voxtral Small 24B 2507?
Voxtral Small 24B 2507 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). Mistral Medium 3.1 costs $0.40 input / $2.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Voxtral Small 24B 2507 versus $0.80 for Mistral Medium 3.1 (5.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Mistral Medium 3.1 has not been scored yet and Voxtral Small 24B 2507 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Medium 3.1 and Voxtral Small 24B 2507 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Mistral Medium 3.1 has the largest context window at 262,144 tokens, against 32,768 for Voxtral Small 24B 2507. Maximum output per response: Mistral Medium 3.1 up to 262,144, Voxtral Small 24B 2507 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Mistral Medium 3.1 accepts text and images; Voxtral Small 24B 2507 accepts text and audio. They handle the same number of input types.
Are any of these open source?
Voxtral Small 24B 2507 publishes its weights (Apache 2.0) and can be self-hosted; Mistral Medium 3.1 is proprietary.
Which is newer?
Mistral Medium 3.1 is the newest, released Aug 12, 2025. Voxtral Small 24B 2507 came out Jul 15, 2025. Knowledge cutoff: Mistral Medium 3.1 May 2025.
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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