command-r
8B parameters
Restricted
Reviewed October 2026

Command R7B (12-2024)

Command R7B (December 2024) is Cohere's smallest model in the Command R family, an 8B-parameter dense transformer with 128K context, trained for retrieval-augmented generation, tool use, and citation generation across 23 languages. It is released under CC-BY-NC-4.0 for research use only; commercial deployment requires Cohere's commercial license.

License: cc-by-nc-4.0·Context: 131,072 tokens
BLK · VERDICT

Our verdict

OP · Eruo Fredoline|UPDATED OCT 7, 2026
Not tested by usEditorial assessment from specifications and published reports.
unrated

Excellent model, dangerous license for most operators. Command R7B is one of the best open weights you can run for citation-grounded RAG and structured tool use at the 7-8B tier.

Overview

Command R7B (December 2024) is Cohere's smallest model in the Command R family, an 8B-parameter dense transformer with 128K context, trained for retrieval-augmented generation, tool use, and citation generation across 23 languages. It is released under CC-BY-NC-4.0 for research use only; commercial deployment requires Cohere's commercial license.

Strengths

  • Best-in-class RAG and citation behavior at its size, by design
  • 128K context with strong long-context retrieval performance
  • Native 23-language coverage including Arabic, Hindi, Vietnamese
  • Tool-use templates are first-class, not bolted on

Weaknesses

  • CC-BY-NC-4.0 BLOCKS commercial use — this is a real trap, not a formality
  • Gated download requires Cohere registration and email signup
  • Listed at 7B but actually 8.03B parameters by safetensors count
  • Switching to Cohere's commercial license is a significant procurement event

Quantization variants

Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.

QuantizationFile sizeVRAM required
Q4_K_M4.4 GB6 GB

Get the model

HuggingFace

Original weights

huggingface.co/CohereLabs/c4ai-command-r7b-12-2024

Source repository — direct quantization required.

Hardware that runs this

Cards with enough VRAM for at least one quantization of Command R7B (12-2024).

Compare alternatives

Models worth comparing

Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.

Frequently asked

What's the minimum VRAM to run Command R7B (12-2024)?

6GB of VRAM is enough to run Command R7B (12-2024) at the Q4_K_M quantization (file size 4.4 GB). Higher-quality quantizations need more.

Can I use Command R7B (12-2024) commercially?

Command R7B (12-2024) is released under the cc-by-nc-4.0, which has restrictions for commercial use. Review the license terms before using it in a product.

What's the context length of Command R7B (12-2024)?

Command R7B (12-2024) supports a context window of 131,072 tokens (about 131K).

Source: huggingface.co/CohereLabs/c4ai-command-r7b-12-2024

Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.

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Before you buy

Verify Command R7B (12-2024) runs on your specific hardware before committing money.