Command R vs Llama-3.2-3B
Too close to call on our weighted score (Command R 51, Llama-3.2-3B 49). The right pick depends on what you value most.
CohereCommand R
51/100- ECI—
- Price$0.15 / $0.60
- Context128K
MetaLlama-3.2-3B
49/100- ECI—
- Price$0.10 / $0.335
- Context131K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 2 points (Command R 51/100, Llama-3.2-3B 49/100), so choose by what matters most for your work: Llama-3.2-3B 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 priceLlama-3.2-3BLlama-3.2-3B $0.159 · Command R $0.263 per 1M tokens (3:1 blend)
- Longest contextLlama-3.2-3BLlama-3.2-3B 131,072 · Command R 128,000 tokens
- Widest inputsSame inputsCommand R: Text · Llama-3.2-3B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Command R | Llama-3.2-3B |
|---|---|---|---|
| Price | 50% | 77 | 88 |
| Inputs & features | 30% | 25 | 0 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 51/100 | 49/100 |
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 RCohere | Llama-3.2-3BMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.15 | $0.10 (best) |
| Output | $0.60 | $0.335 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.263 | $0.159 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Cohere API | Median of 3 providers |
| Limits | ||
| Context window | 128,000 tokens | 131,072 tokens (best) |
| Max output | 4,000 tokens | 8,192 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | No |
| Structured output | No | No |
| Availability | ||
| Weights | Open | OpenLlama 3.2 Community License |
| API model ID | command-r-08-2024 | — |
| API providers | 5 (best) | 3 |
| Released | Aug 30, 2024 | Sep 25, 2024 |
| Knowledge cutoff | Jun 1, 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.
- Command R$2.70
- Llama-3.2-3B$1.67
Which should you choose?
Which is better: Command R or Llama-3.2-3B?
It is close. Our weighted score puts them within 2 points (Command R 51/100, Llama-3.2-3B 49/100), so choose by what matters most for your work: Llama-3.2-3B 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 R or Llama-3.2-3B?
Llama-3.2-3B is cheaper at $0.10 input / $0.335 output per million tokens (median across 3 API providers). Command R costs $0.15 input / $0.60 output per million tokens (official Cohere API price). At a typical mix of three input tokens to one output token, that is $0.159 per million tokens for Llama-3.2-3B versus $0.263 for Command R (1.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Command R 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 Command R 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?
Llama-3.2-3B has the largest context window at 131,072 tokens, against 128,000 for Command R. Maximum output per response: Command R up to 4,000, Llama-3.2-3B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Command R accepts text; Llama-3.2-3B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Llama 3.2 Community License), so you can self-host them.
Which is newer?
Llama-3.2-3B is the newest, released Sep 25, 2024. Command R came out Aug 30, 2024. Knowledge cutoff: Command R Jun 1, 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.
