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Comparison · 3 models · Updated Oct 4, 2026

Nova Micro vs Llama-3.1-8B-Instruct vs Command R7B

Too close to call on our weighted score (Nova Micro 62, Command R7B 62, Llama-3.1-8B-Instruct 56). The right pick depends on what you value most.

  1. Amazon

    Nova Micro

    Released Dec 3, 2024

    62/100
    • ECI—
    • Price$0.035 / $0.14
    • Context128K
    Full specs Remove Nova Micro

  2. Meta

    Llama-3.1-8B-Instruct

    Released Jul 23, 2024

    56/100
    • ECI116.6
    • Price$0.152 / $0.167
    • Context128K
    Full specs Remove Llama-3.1-8B-Instruct

  3. Cohere

    Command R7B

    Released Dec 2, 2024

    62/100
    • ECI—
    • Price$0.037 / $0.15
    • Context128K
    Full specs Remove Command R7B
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Nova Micro 62/100, Command R7B 62/100, Llama-3.1-8B-Instruct 56/100), so choose by what matters most for your work: Nova Micro 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 priceNova MicroNova Micro $0.061 · Command R7B $0.066 · Llama-3.1-8B-Instruct $0.156 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameNova Micro 128,000 · Llama-3.1-8B-Instruct 128,000 · Command R7B 128,000 tokens
  • Widest inputsSame inputsNova Micro: Text · Llama-3.1-8B-Instruct: Text · Command R7B: Text
  • Self-hostingLlama-3.1-8B-Instruct and Command R7BPublishes downloadable weights
How the score is built
MeasureWeightNova MicroLlama-3.1-8B-InstructCommand R7B
Price50%10088100
Inputs & features30%252525
Context window20%242424
Overall100%62/10056/10062/100

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.

Nova Micro vs Llama-3.1-8B-Instruct vs Command R7B specifications side by side
SpecificationNova MicroAmazonLlama-3.1-8B-InstructMetaCommand R7BCohere
Capability
Capabilities Index (ECI)—116.6—
ECI rank—#145 of 148—
GPQA DiamondGraduate-level science questions—27.0%—
OTIS Mock AIME 2024–2025Competition mathematics—1.7%—
Price per million tokens
Input$0.035 (best)$0.152$0.037
Output$0.14 (best)$0.167$0.15
Cached input$0.0088——
Blended (3:1)$0.061 (best)$0.156$0.066
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Amazon Bedrock APIMedian of 9 providersOfficial Cohere API
Limits
Context window128,000 tokens128,000 tokens128,000 tokens
Max output10,000 tokens (best)4,096 tokens4,000 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsProprietaryOpenOpen
API model IDamazon.nova-micro-v1:0—command-r7b-12-2024
API providers39 (best)5
ReleasedDec 3, 2024Jul 23, 2024Dec 2, 2024
Knowledge cutoffOct 2024Dec 2023Jun 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.

  • Nova Micro$0.63
  • Llama-3.1-8B-Instruct$1.85
  • Command R7B$0.675
04 — Questions

Which should you choose?

Which is better: Nova Micro, Llama-3.1-8B-Instruct or Command R7B?

It is close. Our weighted score puts them within a point (Nova Micro 62/100, Command R7B 62/100, Llama-3.1-8B-Instruct 56/100), so choose by what matters most for your work: Nova Micro 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, Nova Micro, Llama-3.1-8B-Instruct or Command R7B?

Nova Micro is cheaper at $0.035 input / $0.14 output per million tokens (official Amazon Bedrock API price). Command R7B costs $0.037 input / $0.15 output per million tokens (official Cohere API price); Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 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 $0.066 for Command R7B (1.1× as much) and $0.156 for Llama-3.1-8B-Instruct (2.5× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Nova Micro has not been scored yet, Llama-3.1-8B-Instruct has an ECI of 116.6 and Command R7B has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Nova Micro, Llama-3.1-8B-Instruct and Command R7B 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?

Nova Micro, Llama-3.1-8B-Instruct and Command R7B share the same 128,000-token context window. Maximum output per response: Nova Micro up to 10,000, Llama-3.1-8B-Instruct up to 4,096, Command R7B up to 4,000 tokens.

Which can read images, PDFs, audio or video?

Nova Micro accepts text; Llama-3.1-8B-Instruct accepts text; Command R7B accepts text. They handle the same number of input types.

Are any of these open source?

Llama-3.1-8B-Instruct and Command R7B publishes its weights and can be self-hosted; Nova Micro is proprietary.

Which is newer?

Nova Micro is the newest, released Dec 3, 2024. Command R7B came out Dec 2, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Nova Micro Oct 2024, Llama-3.1-8B-Instruct Dec 2023, Command R7B 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.

05 — Keep comparing

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