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Comparison · 3 models · Updated Oct 4, 2026

Llama-3.2-11B-Vision-Instruct vs Pixtral 12B vs Command R

Pixtral 12B comes out ahead, 64 to 58 and 51 on our weighted score, and it is the cheaper option too.

  1. Meta

    Llama-3.2-11B-Vision-Instruct

    Released Sep 25, 2024

    58/100
    • ECI—
    • Price$0.197 / $0.51
    • Context128K
  2. Our pick

    Mistral AI

    Pixtral 12B

    Released Sep 1, 2024

    64/100
    • ECI—
    • Price$0.15 / $0.15
    • Context128K
  3. Cohere

    Command R

    Released Aug 30, 2024

    51/100
    • ECI—
    • Price$0.15 / $0.60
    • Context128K
01 — Verdict

Pixtral 12B is our pick

Pixtral 12B is the better all-round choice, scoring 64/100 against Llama-3.2-11B-Vision-Instruct (58) and Command R (51). It leads on price. 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 · 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 · Pixtral 12B 128,000 · Command R 128,000 tokens
  • Widest inputsLlama-3.2-11B-Vision-Instruct and Pixtral 12BLlama-3.2-11B-Vision-Instruct: Text, Images · Pixtral 12B: Text, Images · Command R: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightLlama-3.2-11B-Vision-InstructPixtral 12BCommand R
Price50%768977
Inputs & features30%505025
Context window20%242424
Overall100%58/10064/10051/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Llama-3.2-11B-Vision-Instruct vs Pixtral 12B vs Command R specifications side by side
SpecificationLlama-3.2-11B-Vision-InstructMetaPixtral 12BMistral AICommand RCohere
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.197$0.15 (best)$0.15 (best)
Output$0.51$0.15 (best)$0.60
Cached input———
Blended (3:1)$0.275$0.15 (best)$0.263
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Mistral APIOfficial Cohere API
Limits
Context window128,000 tokens128,000 tokens128,000 tokens
Max output4,096 tokens128,000 tokens (best)4,000 tokens
Inputs and features
TextYesYesYes
ImagesYesYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model ID—pixtral-12bcommand-r-08-2024
API providers245 (best)
ReleasedSep 25, 2024Sep 1, 2024Aug 30, 2024
Knowledge cutoffDec 2023Sep 2024Jun 1, 2024
03 — Cost

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
  • Pixtral 12B$1.80
  • Command R$2.70
04 — Questions

Which should you choose?

Which is better: Llama-3.2-11B-Vision-Instruct, Pixtral 12B or Command R?

Pixtral 12B is the better all-round choice, scoring 64/100 against Llama-3.2-11B-Vision-Instruct (58) and Command R (51). It leads on price. 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, Pixtral 12B or Command R?

Pixtral 12B is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral 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 $0.15 per million tokens for Pixtral 12B versus $0.263 for Command R (1.8× as much) and $0.275 for Llama-3.2-11B-Vision-Instruct (1.8× 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, Pixtral 12B 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, Pixtral 12B 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, Pixtral 12B 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, Pixtral 12B up to 128,000, 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; Pixtral 12B accepts text and images; Command R accepts text. Llama-3.2-11B-Vision-Instruct handles the widest range of inputs.

Are any of these open source?

Yes, all three publish their weights, so you can self-host them.

Which is newer?

Llama-3.2-11B-Vision-Instruct is the newest, released Sep 25, 2024. Pixtral 12B came out Sep 1, 2024; Command R came out Aug 30, 2024. Knowledge cutoff: Llama-3.2-11B-Vision-Instruct Dec 2023, Pixtral 12B Sep 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.