Llama-3.2-11B-Vision-Instruct vs Nova Micro vs Command R
Nova Micro comes out ahead, 62 to 58 and 51 on our weighted score, and it is the cheaper option too.
MetaLlama-3.2-11B-Vision-Instruct
58/100- ECI—
- Price$0.197 / $0.51
- Context128K
- Our pick
AmazonNova Micro
62/100- ECI—
- Price$0.035 / $0.14
- Context128K
CohereCommand R
51/100- ECI—
- Price$0.15 / $0.60
- Context128K
Nova Micro is our pick
Nova Micro is the better all-round choice, scoring 62/100 against Llama-3.2-11B-Vision-Instruct (58) and Command R (51). It leads on price. Llama-3.2-11B-Vision-Instruct wins on inputs & features. 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 priceNova MicroNova Micro $0.061 · Command R $0.263 · Llama-3.2-11B-Vision-Instruct $0.275 per 1M tokens (3:1 blend)
- Longest contextAbout the sameLlama-3.2-11B-Vision-Instruct 128,000 · Nova Micro 128,000 · Command R 128,000 tokens
- Widest inputsLlama-3.2-11B-Vision-InstructLlama-3.2-11B-Vision-Instruct: Text, Images · Nova Micro: Text · Command R: Text
- Self-hostingLlama-3.2-11B-Vision-Instruct and Command RPublishes downloadable weights
| Measure | Weight | Llama-3.2-11B-Vision-Instruct | Nova Micro | Command R |
|---|---|---|---|---|
| Price | 50% | 76 | 100 | 77 |
| Inputs & features | 30% | 50 | 25 | 25 |
| Context window | 20% | 24 | 24 | 24 |
| Overall | 100% | 58/100 | 62/100 | 51/100 |
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-3.2-11B-Vision-InstructMeta | Nova MicroAmazon | Command RCohere |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.197 | $0.035 (best) | $0.15 |
| Output | $0.51 | $0.14 (best) | $0.60 |
| Cached input | — | $0.0088 | — |
| Blended (3:1) | $0.275 | $0.061 (best) | $0.263 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Official Amazon Bedrock API | Official Cohere API |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 128,000 tokens |
| Max output | 4,096 tokens | 10,000 tokens (best) | 4,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| 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 | Open | Proprietary | Open |
| API model ID | — | amazon.nova-micro-v1:0 | command-r-08-2024 |
| API providers | 2 | 3 | 5 (best) |
| Released | Sep 25, 2024 | Dec 3, 2024 | Aug 30, 2024 |
| Knowledge cutoff | Dec 2023 | Oct 2024 | Jun 1, 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-3.2-11B-Vision-Instruct$2.99
- Nova Micro$0.63
- Command R$2.70
Which should you choose?
Which is better: Llama-3.2-11B-Vision-Instruct, Nova Micro or Command R?
Nova Micro is the better all-round choice, scoring 62/100 against Llama-3.2-11B-Vision-Instruct (58) and Command R (51). It leads on price. Llama-3.2-11B-Vision-Instruct wins on inputs & features. 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-3.2-11B-Vision-Instruct, Nova Micro or Command R?
Nova Micro is cheaper at $0.035 input / $0.14 output per million tokens (official Amazon Bedrock API price). Command R costs $0.15 input / $0.60 output per million tokens (official Cohere API price); Llama-3.2-11B-Vision-Instruct costs $0.197 input / $0.51 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.061 per million tokens for Nova Micro versus $0.263 for Command R (4.3× as much) and $0.275 for Llama-3.2-11B-Vision-Instruct (4.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Llama-3.2-11B-Vision-Instruct has not been scored yet, Nova Micro has not been scored yet and Command R has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-11B-Vision-Instruct, Nova Micro and Command R 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?
Llama-3.2-11B-Vision-Instruct, Nova Micro and Command R share the same 128,000-token context window. Maximum output per response: Llama-3.2-11B-Vision-Instruct up to 4,096, Nova Micro up to 10,000, Command R up to 4,000 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-11B-Vision-Instruct accepts text and images; Nova Micro accepts text; Command R accepts text. Llama-3.2-11B-Vision-Instruct handles the widest range of inputs.
Are any of these open source?
Llama-3.2-11B-Vision-Instruct and Command R publishes its weights and can be self-hosted; Nova Micro is proprietary.
Which is newer?
Nova Micro is the newest, released Dec 3, 2024. Llama-3.2-11B-Vision-Instruct came out Sep 25, 2024; Command R came out Aug 30, 2024. Knowledge cutoff: Llama-3.2-11B-Vision-Instruct Dec 2023, Nova Micro Oct 2024, Command R Jun 1, 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.
