Pixtral 12B vs Qwen2.5-VL 7B Instruct
Pixtral 12B comes out ahead, 64 to 51 on our weighted score, and it is the cheaper option too.
- Our pick
Mistral AIPixtral 12B
64/100- ECI—
- Price$0.15 / $0.15
- Context128K
Alibaba (Qwen)Qwen2.5-VL 7B Instruct
51/100- ECI—
- Price$0.35 / $1.05
- Context131K
Add a model
Make it a three-way comparison.
Pixtral 12B is our pick
Pixtral 12B is the better all-round choice, scoring 64/100 against Qwen2.5-VL 7B Instruct (51). It leads on price. 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 pricePixtral 12BPixtral 12B $0.15 · Qwen2.5-VL 7B Instruct $0.525 per 1M tokens (3:1 blend)
- Longest contextQwen2.5-VL 7B InstructQwen2.5-VL 7B Instruct 131,072 · Pixtral 12B 128,000 tokens
- Widest inputsSame inputsPixtral 12B: Text, Images · Qwen2.5-VL 7B Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Pixtral 12B | Qwen2.5-VL 7B Instruct |
|---|---|---|---|
| Price | 50% | 89 | 63 |
| Inputs & features | 30% | 50 | 50 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 64/100 | 51/100 |
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 | Pixtral 12BMistral AI | Qwen2.5-VL 7B InstructAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.15 (best) | $0.35 |
| Output | $0.15 (best) | $1.05 |
| Cached input | — | — |
| Blended (3:1) | $0.15 (best) | $0.525 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Alibaba API |
| Limits | ||
| Context window | 128,000 tokens | 131,072 tokens (best) |
| Max output | 128,000 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | pixtral-12b | qwen2-5-vl-7b-instruct |
| API providers | 4 (best) | 1 |
| Released | Sep 1, 2024 | Sep 2024 |
| Knowledge cutoff | Sep 2024 | 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.
- Pixtral 12B$1.80
- Qwen2.5-VL 7B Instruct$5.60
Which should you choose?
Which is better: Pixtral 12B or Qwen2.5-VL 7B Instruct?
Pixtral 12B is the better all-round choice, scoring 64/100 against Qwen2.5-VL 7B Instruct (51). It leads on price. 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, Pixtral 12B or Qwen2.5-VL 7B Instruct?
Pixtral 12B is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). Qwen2.5-VL 7B Instruct costs $0.35 input / $1.05 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 Pixtral 12B versus $0.525 for Qwen2.5-VL 7B Instruct (3.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Pixtral 12B has not been scored yet and Qwen2.5-VL 7B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Pixtral 12B and Qwen2.5-VL 7B 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 7B Instruct has the largest context window at 131,072 tokens, against 128,000 for Pixtral 12B. Maximum output per response: Pixtral 12B up to 128,000, Qwen2.5-VL 7B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Pixtral 12B accepts text and images; Qwen2.5-VL 7B Instruct accepts text and images. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Pixtral 12B is the newest, released Sep 1, 2024. Qwen2.5-VL 7B Instruct came out Sep 2024. Knowledge cutoff: Pixtral 12B Sep 2024, Qwen2.5-VL 7B 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 Oct 4, 2026.
