Cohere Command R vs GPT-4.1 mini

Cohere Command R is cheaper for every workload modelled here.

List prices checked

Specifications and rates

PropertyCohere Command RGPT-4.1 mini
Input per 1M$0.150$0.400
Output per 1M$0.600$1.60
Cached input per 1M$0.100
Blended (3:1)$0.262$0.700
Context window128K1M
Max output33K
Inputs acceptedtexttext, image

Source: Cohere pricing (May 2026) · OpenAI pricing (May 2026). Published list prices only — committed-use discounts, regional variation, and per-request charges are not included. Not yet independently re-checked against the vendor’s page.

Monthly cost by workload

Identical token volumes through both rate cards. Output-heavy profiles are where the ranking flips.

WorkloadCohere Command RGPT-4.1 miniCheaper
In-app chat assistantA support or help assistant handling a few thousand conversations a month, with short prompts and short answers.$6.00$16Cohere Command Rsaves $10/mo (63%)
RAG over documentsRetrieval-augmented answering where each request stuffs several retrieved passages into the prompt, so input dominates.$54$144Cohere Command Rsaves $90/mo (63%)
Coding agentAn agentic loop that reads files and writes patches, generating heavy output and re-sending large context on every turn.$120$320Cohere Command Rsaves $200/mo (63%)

What each one is for

Cohere Command R

by Cohere

The cheap end of Cohere's range, aimed at retrieval pipelines where the model's job is to ground an answer in supplied documents rather than to reason from scratch.

GPT-4.1 mini

by OpenAI

The million-token context window at a fifth of the price, which is an unusual combination and the main reason this model is still in production stacks.

Common questions

Is Cohere Command R or GPT-4.1 mini cheaper in 2026?
Cohere Command R, for every workload modelled here. On a blended 3:1 basis it costs $0.262 per million tokens against GPT-4.1 mini's $0.700.
Which has the larger context window?
GPT-4.1 mini, at 1M tokens against 128K. A larger window only helps if you can afford to fill it — the cost of one full-context request is in the table above.
Which is cheaper for output-heavy work like agents?
Cohere Command R, at $0.600 per million output tokens against $1.60. Reasoning tokens bill as output, so for agentic loops this axis usually decides the invoice regardless of what the input rates look like.
What is not included in these figures?
Batch-processing discounts, fine-tuning, long-context surcharges above a provider's standard tier, and any enterprise agreement. These are published pay-as-you-go list prices, checked against each provider's own pricing page on the date shown.
Is switching from GPT-4.1 mini to Cohere Command R worth it?
On price alone it is about 63% cheaper on a blended basis. Whether that survives contact with your workload depends on output quality and on retry rate — a cheaper model that needs two attempts is not cheaper. Model the specific volumes in the calculator before you migrate.

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