Voxtral Small 24B 2507 vs Qwen2.5-VL 72B Instruct
Voxtral Small 24B 2507 comes out ahead, 55 to 44 on our weighted score, and it is the cheaper option too.
- Our pick
Mistral AIVoxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.40
- Context33K
Alibaba (Qwen)Qwen2.5-VL 72B Instruct
44/100- ECI—
- Price$0.905 / $1.00
- Context131K
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 Qwen2.5-VL 72B Instruct (44). It leads on price. Qwen2.5-VL 72B Instruct 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 $0.175 · Qwen2.5-VL 72B Instruct $0.93 per 1M tokens (3:1 blend)
- Longest contextQwen2.5-VL 72B InstructQwen2.5-VL 72B Instruct 131,072 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsSame inputsVoxtral Small 24B 2507: Text, Audio · Qwen2.5-VL 72B Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Voxtral Small 24B 2507 | Qwen2.5-VL 72B Instruct |
|---|---|---|---|
| Price | 50% | 82 | 49 |
| Inputs & features | 30% | 45 | 50 |
| Context window | 20% | 0 | 25 |
| Overall | 100% | 55/100 | 44/100 |
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 | Qwen2.5-VL 72B InstructAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.10 (best) | $0.905 |
| Output | $0.40 (best) | $1.00 |
| Cached input | — | — |
| Blended (3:1) | $0.175 (best) | $0.93 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 6 providers |
| Limits | ||
| Context window | 32,768 tokens | 131,072 tokens (best) |
| Max output | 32,768 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | Yes | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | OpenApache 2.0 | Open |
| API model ID | voxtral-small-latest | — |
| API providers | 10 (best) | 6 |
| Released | Jul 15, 2025 | Jan 26, 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$1.80
- Qwen2.5-VL 72B Instruct$11.06
Which should you choose?
Which is better: Voxtral Small 24B 2507 or Qwen2.5-VL 72B Instruct?
Voxtral Small 24B 2507 is the better all-round choice, scoring 55/100 against Qwen2.5-VL 72B Instruct (44). It leads on price. Qwen2.5-VL 72B Instruct 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, Voxtral Small 24B 2507 or Qwen2.5-VL 72B Instruct?
Voxtral Small 24B 2507 is cheaper at $0.10 input / $0.40 output per million tokens (official Mistral API price). Qwen2.5-VL 72B Instruct costs $0.905 input / $1.00 output per million tokens (median across 6 API providers). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for Voxtral Small 24B 2507 versus $0.93 for Qwen2.5-VL 72B Instruct (5.3× 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 Qwen2.5-VL 72B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Voxtral Small 24B 2507 and Qwen2.5-VL 72B Instruct 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?
Qwen2.5-VL 72B Instruct has the largest context window at 131,072 tokens, against 32,768 for Voxtral Small 24B 2507. Maximum output per response: Voxtral Small 24B 2507 up to 32,768, Qwen2.5-VL 72B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Voxtral Small 24B 2507 accepts text and audio; Qwen2.5-VL 72B Instruct accepts text and images. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Voxtral Small 24B 2507 is the newest, released Jul 15, 2025. Qwen2.5-VL 72B Instruct came out Jan 26, 2025. Knowledge cutoff: Qwen2.5-VL 72B Instruct 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 Nov 2, 2026.
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