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Comparison · 3 models · Updated Oct 4, 2026

Llama-3.2-11B-Vision-Instruct vs Aya Expanse 32B vs Command R

Llama-3.2-11B-Vision-Instruct comes out ahead, 58 to 51 and 33 on our weighted score.

  1. Our pick

    Meta

    Llama-3.2-11B-Vision-Instruct

    Released Sep 25, 2024

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

    Aya Expanse 32B

    Released Oct 24, 2024

    33/100
    • ECI—
    • Price$0.50 / $1.50
    • Context128K
  3. Cohere

    Command R

    Released Aug 30, 2024

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

Llama-3.2-11B-Vision-Instruct is our pick

Llama-3.2-11B-Vision-Instruct is the better all-round choice, scoring 58/100 against Command R (51) and Aya Expanse 32B (33). It leads 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 priceCommand RCommand R $0.263 · Llama-3.2-11B-Vision-Instruct $0.275 · Aya Expanse 32B $0.75 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameLlama-3.2-11B-Vision-Instruct 128,000 · Aya Expanse 32B 128,000 · Command R 128,000 tokens
  • Widest inputsLlama-3.2-11B-Vision-InstructLlama-3.2-11B-Vision-Instruct: Text, Images · Aya Expanse 32B: Text · 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-InstructAya Expanse 32BCommand R
Price50%765677
Inputs & features30%50025
Context window20%242424
Overall100%58/10033/10051/100

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 Aya Expanse 32B vs Command R specifications side by side
SpecificationLlama-3.2-11B-Vision-InstructMetaAya Expanse 32BCohereCommand RCohere
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.197$0.50$0.15 (best)
Output$0.51 (best)$1.50$0.60
Cached input———
Blended (3:1)$0.275$0.75$0.263 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersMedian of 1 providersOfficial Cohere API
Limits
Context window128,000 tokens128,000 tokens128,000 tokens
Max output4,096 tokens (best)4,000 tokens4,000 tokens
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesNoYes
Structured outputNoNoNo
Availability
WeightsOpenOpenCC-BY-NC-4.0Open
API model ID—c4ai-aya-expanse-32bcommand-r-08-2024
API providers225 (best)
ReleasedSep 25, 2024Oct 24, 2024Aug 30, 2024
Knowledge cutoffDec 2023—Jun 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
  • Aya Expanse 32B$8.00
  • Command R$2.70
04 — Questions

Which should you choose?

Which is better: Llama-3.2-11B-Vision-Instruct, Aya Expanse 32B or Command R?

Llama-3.2-11B-Vision-Instruct is the better all-round choice, scoring 58/100 against Command R (51) and Aya Expanse 32B (33). It leads 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, Aya Expanse 32B or Command R?

Command R is cheaper at $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); Aya Expanse 32B costs $0.50 input / $1.50 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for Command R versus $0.275 for Llama-3.2-11B-Vision-Instruct (1× as much) and $0.75 for Aya Expanse 32B (2.9× 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, Aya Expanse 32B 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, Aya Expanse 32B and Command R yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Aya Expanse 32B does not support tool calling, which most coding agents need.

Which has the bigger context window?

Llama-3.2-11B-Vision-Instruct, Aya Expanse 32B 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, Aya Expanse 32B up to 4,000, 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; Aya Expanse 32B accepts text; 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 (CC-BY-NC-4.0), so you can self-host them.

Which is newer?

Aya Expanse 32B is the newest, released Oct 24, 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, 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.