Voxtral Small 24B 2507 vs Qwen-MT Turbo
Voxtral Small 24B 2507 comes out ahead, 55 to 40 on our weighted score, and it is the cheaper option too.
- Our pick
Mistral AIVoxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.30
- Context33K
Alibaba (Qwen)Qwen-MT Turbo
40/100- ECI—
- Price$0.16 / $0.49
- Context16K
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 Qwen-MT Turbo (40). It leads on price and inputs & features. 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 · Qwen-MT Turbo $0.242 per 1M tokens (3:1 blend)
- Longest contextVoxtral Small 24B 2507Voxtral Small 24B 2507 32,768 · Qwen-MT Turbo 16,384 tokens
- Widest inputsVoxtral Small 24B 2507Voxtral Small 24B 2507: Text, Audio · Qwen-MT Turbo: Text
- Self-hostingVoxtral Small 24B 2507Publishes downloadable weights (Apache 2.0)
| Measure | Weight | Voxtral Small 24B 2507 | Qwen-MT Turbo |
|---|---|---|---|
| Price | 50% | 89 | 79 |
| Inputs & features | 30% | 35 | 0 |
| Context window | 20% | 0 | 0 |
| Overall | 100% | 55/100 | 40/100 |
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 | Voxtral Small 24B 2507Mistral AI | Qwen-MT TurboAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.10 (best) | $0.16 |
| Output | $0.30 (best) | $0.49 |
| Cached input | — | — |
| Blended (3:1) | $0.15 (best) | $0.242 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Alibaba API |
| Limits | ||
| Context window | 32,768 tokens (best) | 16,384 tokens |
| Max output | 32,768 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | Yes | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | No |
| Structured output | No | No |
| Availability | ||
| Weights | OpenApache 2.0 | Proprietary |
| API model ID | voxtral-small-latest | qwen-mt-turbo |
| API providers | 7 (best) | 1 |
| Released | Jul 15, 2025 | Jan 2025 |
| Knowledge cutoff | — | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Voxtral Small 24B 2507$1.60
- Qwen-MT Turbo$2.58
Which should you choose?
Which is better: Voxtral Small 24B 2507 or Qwen-MT Turbo?
Voxtral Small 24B 2507 is the better all-round choice, scoring 55/100 against Qwen-MT Turbo (40). It leads on price and inputs & features. 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, Voxtral Small 24B 2507 or Qwen-MT Turbo?
Voxtral Small 24B 2507 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). Qwen-MT Turbo costs $0.16 input / $0.49 output per million tokens (official Alibaba 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 $0.242 for Qwen-MT Turbo (1.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Voxtral Small 24B 2507 has not been scored yet and Qwen-MT Turbo has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Voxtral Small 24B 2507 and Qwen-MT Turbo yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-MT Turbo does not support tool calling, which most coding agents need.
Which has the bigger context window?
Voxtral Small 24B 2507 has the largest context window at 32,768 tokens, against 16,384 for Qwen-MT Turbo. Maximum output per response: Voxtral Small 24B 2507 up to 32,768, Qwen-MT Turbo up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Voxtral Small 24B 2507 accepts text and audio; Qwen-MT Turbo accepts text. Voxtral Small 24B 2507 handles the widest range of inputs.
Are any of these open source?
Voxtral Small 24B 2507 publishes its weights (Apache 2.0) and can be self-hosted; Qwen-MT Turbo is proprietary.
Which is newer?
Voxtral Small 24B 2507 is the newest, released Jul 15, 2025. Qwen-MT Turbo came out Jan 2025. Knowledge cutoff: Qwen-MT Turbo Apr 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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