solar-mini vs Qwen2.5-VL 7B Instruct vs Pixtral 12B
Pixtral 12B comes out ahead, 64 to 52 and 51 on our weighted score.
Upstage
solar-mini
52/100- ECI—
- Price$0.15 / $0.15
- Context33K
Alibaba (Qwen)Qwen2.5-VL 7B Instruct
51/100- ECI—
- Price$0.35 / $1.05
- Context131K
- Our pick
Mistral AIPixtral 12B
64/100- ECI—
- Price$0.15 / $0.15
- Context128K
Pixtral 12B is our pick
Pixtral 12B is the better all-round choice, scoring 64/100 against solar-mini (52) and Qwen2.5-VL 7B Instruct (51). 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 pricesolar-mini and Pixtral 12Bsolar-mini $0.15 · Pixtral 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 · solar-mini 32,768 tokens
- Widest inputsQwen2.5-VL 7B Instruct and Pixtral 12Bsolar-mini: Text · Qwen2.5-VL 7B Instruct: Text, Images · Pixtral 12B: Text, Images
- Self-hostingQwen2.5-VL 7B Instruct and Pixtral 12BPublishes downloadable weights
| Measure | Weight | solar-mini | Qwen2.5-VL 7B Instruct | Pixtral 12B |
|---|---|---|---|---|
| Price | 50% | 89 | 63 | 89 |
| Inputs & features | 30% | 25 | 50 | 50 |
| Context window | 20% | 0 | 24 | 24 |
| Overall | 100% | 52/100 | 51/100 | 64/100 |
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 | solar-miniUpstage | Qwen2.5-VL 7B InstructAlibaba (Qwen) | Pixtral 12BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.15 (best) | $0.35 | $0.15 (best) |
| Output | $0.15 (best) | $1.05 | $0.15 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.15 (best) | $0.525 | $0.15 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Upstage API | Official Alibaba API | Official Mistral API |
| Limits | |||
| Context window | 32,768 tokens | 131,072 tokens (best) | 128,000 tokens |
| Max output | 4,096 tokens | 8,192 tokens | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | solar-mini | qwen2-5-vl-7b-instruct | pixtral-12b |
| API providers | 1 | 1 | 4 (best) |
| Released | Jun 12, 2024 | Sep 2024 | Sep 1, 2024 |
| Knowledge cutoff | Sep 2024 | Apr 2024 | Sep 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- solar-mini$1.80
- Qwen2.5-VL 7B Instruct$5.60
- Pixtral 12B$1.80
Which should you choose?
Which is better: solar-mini, Qwen2.5-VL 7B Instruct or Pixtral 12B?
Pixtral 12B is the better all-round choice, scoring 64/100 against solar-mini (52) and Qwen2.5-VL 7B Instruct (51). 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, solar-mini, Qwen2.5-VL 7B Instruct or Pixtral 12B?
solar-mini is cheaper at $0.15 input / $0.15 output per million tokens (official Upstage API price). Pixtral 12B costs $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 solar-mini versus $0.15 for Pixtral 12B (1× as much) and $0.525 for Qwen2.5-VL 7B Instruct (3.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. solar-mini has not been scored yet, Qwen2.5-VL 7B Instruct has not been scored yet and Pixtral 12B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for solar-mini, Qwen2.5-VL 7B Instruct and Pixtral 12B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three 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 and 32,768 for solar-mini. Maximum output per response: solar-mini up to 4,096, Qwen2.5-VL 7B Instruct up to 8,192, Pixtral 12B up to 128,000 tokens.
Which can read images, PDFs, audio or video?
solar-mini accepts text; Qwen2.5-VL 7B Instruct accepts text and images; Pixtral 12B accepts text and images. Qwen2.5-VL 7B Instruct handles the widest range of inputs.
Are any of these open source?
Qwen2.5-VL 7B Instruct and Pixtral 12B publishes its weights and can be self-hosted; solar-mini is proprietary.
Which is newer?
Qwen2.5-VL 7B Instruct is the newest, released Sep 2024. Pixtral 12B came out Sep 1, 2024; solar-mini came out Jun 12, 2024. Knowledge cutoff: solar-mini Sep 2024, Qwen2.5-VL 7B Instruct Apr 2024, Pixtral 12B Sep 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.
