What is Command R7B (12-2024) API?
Command R7B (12-2024) is available through AIMLAPI.
Technical Specifications
- Supported inputs: Image, Text
- Output: Text
- Context window: 128,000 tokens / Max output: 4,000 tokens
- Endpoint: /chat/completions
Performance Benchmarks
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Command R7B (12-2024) API Pricing
- Input: $0.04875 / 1M tokens
- Output: $0.195 / 1M tokens
Where to Use Command R7B (12-2024)
Coding and code review
Generate, debug, and review code across languages, reading whole files or repos in a single prompt.
Agentic and multi-step workflows
Reliable tool-calling and instruction-following suit agent loops that plan, call tools, and iterate.
Complex reasoning
Extended reasoning improves reliability on multi-step math, logic, and technical analysis.
Long-document analysis
Summarize and extract from contracts, papers, and reports without aggressive chunking.
Code Sample
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Measured on the AI/ML API gateway across live traffic. Figures are medians unless stated. Last updated 2026-10-12.
Command R7B (12-2024) is documented as suited for retrieval-augmented generation (RAG), where outputs are grounded in external data sources to improve accuracy.
It is also suited for tool use, including real-world workflows that involve search engines, APIs, vector databases, and avoiding unnecessary tool calls.
The model is documented for agentic applications, especially fast REACT-style agents that break complex questions into subgoals and perform active information seeking.
It is also described as strong for high-throughput, latency-sensitive applications such as chatbots and code assistants.
import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "cohere/command-r7b-12-2024", "messages": [ { "role": "user", "content": "Hello!" } ] }, ) print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", { method: "POST", headers: { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ "model": "cohere/command-r7b-12-2024", "messages": [ { "role": "user", "content": "Hello!" } ] }), }); console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"cohere/command-r7b-12-2024","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Benchmark | Score | What it measures | Source | Retrieved |
|---|---|---|---|---|
| MMLU-Pro | 28.5 | Multi-discipline knowledge + reasoning (harder MMLU) | Source | September 21, 2026 |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Command R7B (12-2024) This page | Reasoning + agents | |||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
Command R7B (12-2024) has a 128,000 tokens context window and can return up to 4,000 tokens.
Command R7B (12-2024) takes image, text as input and returns text.
Use cohere/command-r7b-12-2024 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Command R7B (12-2024) is priced at input $0.0515775 / 1M tokens, output $0.20631 / 1M tokens.
Yes, Command R7B (12-2024) can stream responses as they are generated.
Yes, Command R7B (12-2024) accepts image input alongside text.
Command R7B (12-2024) was built by Cohere.
Yes, it supports tools, parallel tool calls, and function calling.