Llama-3.2-3B vs Qwen3-Coder 480B-A35B Instruct vs Pixtral 12B
Pixtral 12B comes out ahead, 64 to 49 and 28 on our weighted score, and it is the cheaper option too.
MetaLlama-3.2-3B
49/100- ECI—
- Price$0.10 / $0.335
- Context131K
Alibaba (Qwen)Qwen3-Coder 480B-A35B Instruct
28/100- ECI—
- Price$1.50 / $7.50
- Context262K
- 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 Llama-3.2-3B (49) and Qwen3-Coder 480B-A35B Instruct (28). It leads on inputs & features. Qwen3-Coder 480B-A35B Instruct wins on 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 pricePixtral 12BPixtral 12B $0.15 · Llama-3.2-3B $0.159 · Qwen3-Coder 480B-A35B Instruct $3.00 per 1M tokens (3:1 blend)
- Longest contextQwen3-Coder 480B-A35B InstructQwen3-Coder 480B-A35B Instruct 262,144 · Llama-3.2-3B 131,072 · Pixtral 12B 128,000 tokens
- Widest inputsPixtral 12BLlama-3.2-3B: Text · Qwen3-Coder 480B-A35B Instruct: Text · Pixtral 12B: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama-3.2-3B | Qwen3-Coder 480B-A35B Instruct | Pixtral 12B |
|---|---|---|---|---|
| Price | 50% | 88 | 27 | 89 |
| Inputs & features | 30% | 0 | 25 | 50 |
| Context window | 20% | 24 | 37 | 24 |
| Overall | 100% | 49/100 | 28/100 | 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 | Llama-3.2-3BMeta | Qwen3-Coder 480B-A35B InstructAlibaba (Qwen) | Pixtral 12BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 (best) | $1.50 | $0.15 |
| Output | $0.335 | $7.50 | $0.15 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.159 | $3.00 | $0.15 (best) |
| Long-context rate | Same rate | Over 32K: $2.70 / $13.50 | Same rate |
| Price source | Median of 3 providers | Official Alibaba API | Official Mistral API |
| Limits | |||
| Context window | 131,072 tokens | 262,144 tokens (best) | 128,000 tokens |
| Max output | 8,192 tokens | 65,536 tokens | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenLlama 3.2 Community License | Open | Open |
| API model ID | — | qwen3-coder-480b-a35b-instruct | pixtral-12b |
| API providers | 3 | 7 (best) | 4 |
| Released | Sep 25, 2024 | Apr 2025 | Sep 1, 2024 |
| Knowledge cutoff | Dec 2023 | Apr 2025 | 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.
- Llama-3.2-3B$1.67
- Qwen3-Coder 480B-A35B Instruct$30.00
- Pixtral 12B$1.80
Which should you choose?
Which is better: Llama-3.2-3B, Qwen3-Coder 480B-A35B Instruct or Pixtral 12B?
Pixtral 12B is the better all-round choice, scoring 64/100 against Llama-3.2-3B (49) and Qwen3-Coder 480B-A35B Instruct (28). It leads on inputs & features. Qwen3-Coder 480B-A35B Instruct wins on 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, Llama-3.2-3B, Qwen3-Coder 480B-A35B Instruct or Pixtral 12B?
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); Qwen3-Coder 480B-A35B Instruct costs $1.50 input / $7.50 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 $0.159 for Llama-3.2-3B (1.1× as much) and $3.00 for Qwen3-Coder 480B-A35B Instruct (20× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Llama-3.2-3B has not been scored yet, Qwen3-Coder 480B-A35B 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 Llama-3.2-3B, Qwen3-Coder 480B-A35B Instruct and Pixtral 12B 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?
Qwen3-Coder 480B-A35B Instruct has the largest context window at 262,144 tokens, against 131,072 for Llama-3.2-3B and 128,000 for Pixtral 12B. Maximum output per response: Llama-3.2-3B up to 8,192, Qwen3-Coder 480B-A35B Instruct up to 65,536, Pixtral 12B up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-3B accepts text; Qwen3-Coder 480B-A35B Instruct accepts text; Pixtral 12B accepts text and images. Pixtral 12B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Llama 3.2 Community License), so you can self-host them.
Which is newer?
Qwen3-Coder 480B-A35B Instruct is the newest, released Apr 2025. Llama-3.2-3B came out Sep 25, 2024; Pixtral 12B came out Sep 1, 2024. Knowledge cutoff: Llama-3.2-3B Dec 2023, Qwen3-Coder 480B-A35B Instruct Apr 2025, 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.
