cohere

Cohere: Command R7B (12-2024)

cohere/command-r7b-12-2024

Our take

AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.

OpenRouter’s catalog presents Cohere’s Command R7B (12-2024) as a compact, fast text model released in December 2024. The catalog says it targets RAG, tool use, agents, and other workflows involving complex reasoning, while exposing a 128,000-token context window, an August 31, 2024 knowledge cutoff, structured-output controls, and tool selection. Only catalog evidence was supplied; no independent model card or measured performance results were available for this profile.[1]

Strengths

Catalog-positioned for RAG, tool use, agents, and complex-reasoning workflows.[1]
Offers a 128,000-token context window for text input and output.[1]
Supports structured outputs, tool selection, and common sampling controls.[1]

Limitations

Evidence is catalog-only; no independent model card, benchmarks, or safety details were supplied.[1]
Reasoning metadata is unspecified, so claimed reasoning suitability requires workload validation.[1]

Where to use it

Consider evaluating it for retrieval-augmented assistants that need long context.[1]
A candidate for tool-calling or agent prototypes requiring structured text outputs.[1]

Sources

[1] OpenRouter catalog · Cohere: Command R7B (12-2024)Sources checked: Nov 13, 2026

About this model

Description below is the original text supplied by OpenRouter, shown in the source language.

Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning...

Specifications

Model ID: cohere/command-r7b-12-2024
Creator: cohere
Added to OpenRouter: 14.12.2024
Context length: 128,000
Modality: text->text
Input modalities: text
Output modalities: text
Token pricing: USD per 1M tokens: in $0.037 / out $0.150
Knowledge cutoff: 31.08.2024
Expiration date: —

Tasks and capabilities

A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.

Task	Grade	Source-declared capability
General quality	No measurement	—
Coding	No measurement	—
Agents	No measurement	parameters: structured_outputs, tool_choice, tools
Writing	No measurement	output: text
Reasoning	No measurement	—
Document analysis	No measurement	—
Vision	No measurement	—
Image generation	No measurement	—
Audio	No measurement	—
Video	No measurement	—
Embeddings	No measurement	—

Evaluations

No evaluations are supplied for this model.

How grades work

Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.

S — S — top 10% of the cohort
A — A — next 20% of the cohort
B — B — next 30% of the cohort
C — C — below the B band

Providers

Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.

Provider	Context length	Price in /1M	Price out /1M	Latency p50 (30m, s)	Throughput p50 (30m, tok/s)	Uptime (30m)
Cohere	128,000	$0.037	$0.150	—	—	—

Provider data retrieved: 13.11.2026

No published articles identify this model yet.