command-a-vision-07-2025

command-a-vision-07-2025 is a advanced-tier language model from Cohere. command-a-vision-07-2025 is a proprietary model available exclusively through Cohere's API. Command is Cohere's enterprise-focused model family, with strong retrieval-augmented generation (RAG) performance and native tool use — widely used in enterprise search and document Q&A applications.

command-a-vision-07-2025 does not have a publicly listed price. See Cohere's pricing page for current rates.

Its 128K-token context window handles most long-document tasks — roughly 75,000 words or a full novel — without requiring chunking or retrieval augmentation. Median latency (P50 time-to-first-token) is approximately 700ms — suitable for interactive applications where sub-second response is acceptable. Throughput is approximately 90 tokens/second — adequate for streaming at comfortable reading speed. Maximum output length is 8K tokens — adequate for most generation tasks including essays, code functions, and detailed responses.

command-a-vision-07-2025 is best suited to vision, self-hosted. Supported capabilities include vision inputs (images alongside text), streaming token output for real-time UIs. Vision support enables document analysis, screenshot understanding, diagram interpretation, and visual question answering — images are converted to tokens at the standard input rate based on resolution. When evaluating this model for a specific workload, the most important factors are: context window (does your input fit?), output price (how long are your generations?), and latency (is this interactive or batch?). The pricing table above shows how command-a-vision-07-2025 compares to similar models across these dimensions.

command-a-vision-07-2025 sits in the advanced tier — strong general-purpose models balancing capability and cost, suitable for most production applications. Unlike open-weights alternatives, command-a-vision-07-2025 is only available via Cohere's API — there is no self-hosted option, which simplifies deployment but creates vendor dependency. When comparing command-a-vision-07-2025 to alternatives, use the similar models section on this page to find models at comparable price points with different capability tradeoffs. The intelligence score (78/100) reflects aggregate benchmark performance — a useful proxy for general capability, though real-world performance varies significantly by task type. Always test with your specific prompts and use case before committing to a model for production.