Command R7B (12-2024)
VerifiedCohere's open-weight LLM built for long-context text tasks.
About Command R7B (12-2024)
Command R7B (12-2024) is released with open weights, allowing users to run and fine-tune the model locally or on their own infrastructure. Its 128000-token context window enables processing of lengthy documents, codebases, or conversation histories without truncation.
Developed by Cohere, the model follows the Command series design focused on practical text applications. It accepts and produces text only, making it suitable for chat interfaces, summarization pipelines, and retrieval-augmented workflows.
Typical usage includes enterprise document analysis, customer support automation, and research assistance where extended context improves coherence and accuracy.
Capabilities
How Command R7B (12-2024) compares
Command R7B (12-2024) (striped bar) vs other language models on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · Command R7B (12-2024) ranks #18 of 141
Nova Micro 1.0Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Long-Document Analysis
Command R7B excels at long-context reasoning over 128k tokens, making it suitable for reviewing extensive reports, legal documents, or research papers in a single pass.
RAG-Powered Knowledge Systems
Its retrieval-augmented generation and tool use capabilities support building accurate question-answering systems that pull from external databases or documents.
Multilingual Conversational Agents
The model handles multilingual text generation and instruction following, enabling reliable chatbots or summarization tools across multiple languages.
Strengths & limitations
Strengths
- +Strong RAG optimization
- +Efficient handling of 128k context
- +Cost-effective for production use
- +Reliable instruction adherence
Limitations
- –Text-only modality
- –Smaller scale limits depth on complex tasks
- –Standard LLM hallucination risks
Cost calculator
Estimate what Command R7B (12-2024) would cost for your usage.
Based on Command R7B (12-2024)'s $0.04/1M input · $0.15/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "cohere/command-r7b-12-2024",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: cohere/command-r7b-12-2024
Editor's verdict
Command R7B (12-2024) is Cohere's open-weight language models with a 128K-token context window.
At $0.15 per 1M output tokens, it is very cost-efficient for its class.
As an open-weight model you can self-host it or call it through a hosted API.
Best suited to strong rag optimization and efficient handling of 128k context.
Frequently asked questions
The model supports a context window of 128000 tokens.
User reviews
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