Pixtral 12B vs Vision Large vs Llama-3.2-3B
Vision Large comes out ahead, 84 to 40 and 10 on our weighted score.
Mistral AIPixtral 12B
40/100- ECI—
- Price$0.15 / $0.15
- Context128K
- Our pick
VisparkVision Large
84/100- ECI—
- Price—
- Context1M
MetaLlama-3.2-3B
10/100- ECI—
- Price$0.10 / $0.335
- Context131K
Vision Large is our pick
Vision Large is the better all-round choice, scoring 84/100 against Pixtral 12B (40) and Llama-3.2-3B (10). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. 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 · Llama-3.2-3B $0.159 per 1M tokens (3:1 blend) · Vision Large unpriced
- Longest contextVision LargeVision Large 1,000,000 · Llama-3.2-3B 131,072 · Pixtral 12B 128,000 tokens
- Widest inputsVision LargePixtral 12B: Text, Images · Vision Large: Text, Images, PDFs, Audio, Video · Llama-3.2-3B: Text
- Self-hostingPixtral 12B and Llama-3.2-3BPublishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | Pixtral 12B | Vision Large | Llama-3.2-3B |
|---|---|---|---|---|
| Inputs & features | 60% | 50 | 100 | 0 |
| Context window | 40% | 24 | 60 | 24 |
| Overall | 100% | 40/100 | 84/100 | 10/100 |
Left out because at least one model lacks the data: capability and price. 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 | Vision LargeVispark | Llama-3.2-3BMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.15 | — | $0.10 (best) |
| Output | $0.15 (best) | — | $0.335 |
| Cached input | — | — | — |
| Blended (3:1) | $0.15 (best) | — | $0.159 |
| Long-context rate | Same rate | — | Same rate |
| Price source | Official Mistral API | — | Median of 3 providers |
| Limits | |||
| Context window | 128,000 tokens | 1,000,000 tokens (best) | 131,072 tokens |
| Max output | 128,000 tokens (best) | 65,536 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | No |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | OpenLlama 3.2 Community License |
| API model ID | pixtral-12b | — | — |
| API providers | 4 (best) | — | 3 |
| Released | Sep 1, 2024 | May 15, 2024 | Sep 25, 2024 |
| Knowledge cutoff | Sep 2024 | — | Dec 2023 |
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
- Vision Large—
- Llama-3.2-3B$1.67
Which should you choose?
Which is better: Pixtral 12B, Vision Large or Llama-3.2-3B?
Vision Large is the better all-round choice, scoring 84/100 against Pixtral 12B (40) and Llama-3.2-3B (10). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Pixtral 12B, Vision Large or Llama-3.2-3B?
Pixtral 12B is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). Llama-3.2-3B costs $0.10 input / $0.335 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Pixtral 12B versus $0.159 for Llama-3.2-3B (1.1× as much). Vision Large has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Pixtral 12B has not been scored yet, Vision Large has not been scored yet and Llama-3.2-3B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Pixtral 12B, Vision Large and Llama-3.2-3B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Llama-3.2-3B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Vision Large has the largest context window at 1,000,000 tokens, against 131,072 for Llama-3.2-3B and 128,000 for Pixtral 12B. Maximum output per response: Pixtral 12B up to 128,000, Vision Large up to 65,536, Llama-3.2-3B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Pixtral 12B accepts text and images; Vision Large accepts text, images, PDFs, audio and video; Llama-3.2-3B accepts text. Vision Large handles the widest range of inputs.
Are any of these open source?
Pixtral 12B and Llama-3.2-3B publishes its weights (Llama 3.2 Community License) and can be self-hosted; Vision Large is proprietary.
Which is newer?
Llama-3.2-3B is the newest, released Sep 25, 2024. Pixtral 12B came out Sep 1, 2024; Vision Large came out May 15, 2024. Knowledge cutoff: Pixtral 12B Sep 2024, Llama-3.2-3B Dec 2023.
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.
