Command A Vision: context, capabilities and where to run it
Prices from official vendor price lists · October 2026
Cohere bills Command A Vision per instance-hour, not per token, so a price per million tokens does not exist for this model. Recorded for vision, reasoning.
Capabilities
Context window
128K tokens
Price / mo
API only
Command A Vision is an AI model from Cohere. The vendor does not publish a public per-token price, so the cost cells are left empty rather than guessed.
It holds 128K tokens in a single conversation. Capabilities recorded in this rating: text & chat, vision, reasoning, tool calling, multilingual. Access is through the API rather than a consumer subscription.
API priceNot publishedper 1M tokens, in / out
Context128K tokenstokens per conversation
VendorCohereall models from this vendor
TierUnpricedno public rate card
Compared with alternatives
How Command A Vision sits against its neighbours in this rating. Tap a card to open that model.
Good and poor fit
Good fit
- Multi-step analysis, planning and code review, where the first plausible answer is often wrong.
- Reading screenshots, charts, scanned documents and photos.
Poor fit
- Work where the vendor does not publish a rate you can budget against.
Related filters
Text & chat234 models for text generation and chat
Vision159 models that read images
Reasoning175 models that think before answering
Tool calling172 models that call your functions
MultilingualAll 245 models work beyond English
Cohere8 models from this vendor
All 245 modelsThe full rating with filters and prices
Frequently asked questions
How much does Command A Vision cost?
Cohere does not publish a public per-token rate for this model, so the price cells here are empty rather than estimated.
What is the context window of Command A Vision?
128K tokens in a single conversation.
What can Command A Vision do?
In this rating it is recorded with: text & chat, vision, reasoning, tool calling, multilingual, proprietary API.
Is Command A Vision a good choice?
It depends on the job. See the good-fit and poor-fit lists above, and compare against the neighbouring models before committing.
Frequently searched
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