Cohere • LLM
Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning...
Context Window
128K tokens
Input Price/1M
$0.04
Output Price/1M
$0.15
Parameters
—
Max Output
4K tokens
Cohere: Command R7B (12-2024) results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 4.8 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MATH-500 | 16.4 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 7.4 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 33.8 | 100.0 | Artificial Analysis official API |
| GPQA Diamond | 28.4 | 100.0 | Artificial Analysis official API |
Cohere: Command R7B (12-2024) is an AI model developed by Cohere, classified as a large language model (LLM). It focuses on text processing and natural language generation. As a proprietary model, it is available via Cohere's cloud API. With a context window of 128K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Cohere: Command R7B (12-2024) is usage-based, priced at $0.0375/1M input tokens and $0.15/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Cohere: Command R7B (12-2024) was evaluated on 5 different benchmarks, covering categories like Coding, Math, overall, Reasoning. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Cohere: Command R7B (12-2024) is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
In the 2026 AI model ecosystem, Cohere: Command R7B (12-2024) competes directly with similarly capable models. Cohere competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning...
Cohere: Command R7B (12-2024) costs $0.0375/1M input tokens and $0.15/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
In available benchmarks, Cohere: Command R7B (12-2024) scored: LiveCodeBench: 4.8/100, MATH-500: 16.4/100, AA Intelligence Index: 7.4/100. See the full table above for a detailed comparison.
No, Cohere: Command R7B (12-2024) is a proprietary model from Cohere. It is available via cloud API. For open source alternatives, check our open source model ranking.
Cohere: Command R7B (12-2024) excels at general-purpose language tasks. With its large context window, it handles long documents, codebases, and extended conversations.
Last updated: May 24, 2026 • View methodology →