Command R7B vs Llama-3.2-3B vs Pixtral 12B
Too close to call on our weighted score (Pixtral 12B 64, Command R7B 62, Llama-3.2-3B 49). The right pick depends on what you value most.
CohereCommand R7B
62/100- ECI—
- Price$0.037 / $0.15
- Context128K
MetaLlama-3.2-3B
49/100- ECI—
- Price$0.10 / $0.335
- Context131K
Mistral AIPixtral 12B
64/100- ECI—
- Price$0.15 / $0.15
- Context128K
Too close to call
It is close. Our weighted score puts them within 2 points (Pixtral 12B 64/100, Command R7B 62/100, Llama-3.2-3B 49/100), so choose by what matters most for your work: Command R7B on price and Llama-3.2-3B for long inputs. 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 priceCommand R7BCommand R7B $0.066 · Pixtral 12B $0.15 · Llama-3.2-3B $0.159 per 1M tokens (3:1 blend)
- Longest contextLlama-3.2-3BLlama-3.2-3B 131,072 · Command R7B 128,000 · Pixtral 12B 128,000 tokens
- Widest inputsPixtral 12BCommand R7B: Text · Llama-3.2-3B: Text · Pixtral 12B: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Command R7B | Llama-3.2-3B | Pixtral 12B |
|---|---|---|---|---|
| Price | 50% | 100 | 88 | 89 |
| Inputs & features | 30% | 25 | 0 | 50 |
| Context window | 20% | 24 | 24 | 24 |
| Overall | 100% | 62/100 | 49/100 | 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 | Command R7BCohere | Llama-3.2-3BMeta | Pixtral 12BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.037 (best) | $0.10 | $0.15 |
| Output | $0.15 (best) | $0.335 | $0.15 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.066 (best) | $0.159 | $0.15 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Cohere API | Median of 3 providers | Official Mistral API |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens (best) | 128,000 tokens |
| Max output | 4,000 tokens | 8,192 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 | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | OpenLlama 3.2 Community License | Open |
| API model ID | command-r7b-12-2024 | — | pixtral-12b |
| API providers | 5 (best) | 3 | 4 |
| Released | Dec 2, 2024 | Sep 25, 2024 | Sep 1, 2024 |
| Knowledge cutoff | Jun 1, 2024 | Dec 2023 | 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.
- Command R7B$0.675
- Llama-3.2-3B$1.67
- Pixtral 12B$1.80
Which should you choose?
Which is better: Command R7B, Llama-3.2-3B or Pixtral 12B?
It is close. Our weighted score puts them within 2 points (Pixtral 12B 64/100, Command R7B 62/100, Llama-3.2-3B 49/100), so choose by what matters most for your work: Command R7B on price and Llama-3.2-3B for long inputs. 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, Command R7B, Llama-3.2-3B or Pixtral 12B?
Command R7B is cheaper at $0.037 input / $0.15 output per million tokens (official Cohere API price). Pixtral 12B costs $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 $0.066 per million tokens for Command R7B versus $0.15 for Pixtral 12B (2.3× as much) and $0.159 for Llama-3.2-3B (2.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Command R7B has not been scored yet, Llama-3.2-3B 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 Command R7B, Llama-3.2-3B 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?
Llama-3.2-3B has the largest context window at 131,072 tokens, against 128,000 for Command R7B and 128,000 for Pixtral 12B. Maximum output per response: Command R7B up to 4,000, Llama-3.2-3B up to 8,192, Pixtral 12B up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Command R7B accepts text; Llama-3.2-3B 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?
Command R7B is the newest, released Dec 2, 2024. Llama-3.2-3B came out Sep 25, 2024; Pixtral 12B came out Sep 1, 2024. Knowledge cutoff: Command R7B Jun 1, 2024, Llama-3.2-3B Dec 2023, 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.
