# Command R7B API Pricing

As of October 10, 2026, Command R7B costs $0.0375 per 1M input tokens and $0.15 per 1M output tokens on Cohere. It has a 128,000-token context window and returns up to 4,096 tokens per response.

- Page: https://models.litellm.ai/models/command-r7b
- Lab: Cohere
- LiteLLM model name: `command-r7b-12-2024`
- Context window: 128,000 tokens
- Max output: 4,096 tokens
- Added to LiteLLM: January 2025
- Prices updated: October 10, 2026

## Pricing by provider

Token prices in USD per 1M tokens.

| Provider | Model name | Input | Output | Cache read | Per image | Per second | Context |
|---|---|---|---|---|---|---|---|
| Cohere (snapshot 12-2024) | `command-r7b-12-2024` | $0.0375 | $0.15 | – | – | – | 128K |

## Cost examples

1,000 requests with 2,000 input and 500 output tokens each:

- Cohere: $0.15

100 long-document requests with 100,000 input and 2,000 output tokens each:

- Cohere: $0.405

## Features

Supported: Function calling.

## Use it with LiteLLM

```python
from litellm import completion

response = completion(
    model="command-r7b-12-2024",
    messages=[{"role": "user", "content": "Hello!"}],
)
```

## FAQ

### How much does Command R7B cost?

Command R7B costs $0.0375 per 1M input tokens and $0.15 per 1M output tokens on Cohere.

### What is the context window of Command R7B?

Command R7B has a 128,000-token context window and returns up to 4,096 tokens per response.

### Which providers offer Command R7B?

Command R7B is available from Cohere through LiteLLM, using the model name command-r7b-12-2024.

### How do I call Command R7B with an OpenAI-compatible API?

Use the LiteLLM Python SDK with model="command-r7b-12-2024", or add the model to the LiteLLM proxy's config.yaml and send requests to /v1/chat/completions from any OpenAI client. LiteLLM tracks the cost of every request at the prices on this page.

### What features does Command R7B support?

Command R7B supports function calling.

### When did LiteLLM add Command R7B?

Command R7B was added to LiteLLM's model price file in January 2025.

Source: LiteLLM model price file, https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json