Command R+

Latest
Cohere Command R Generally Available Aug 2024

Cohere's enterprise-grade 104B model optimised for RAG and multi-step tool use. 128K context, strong multilingual retrieval, and built-in citation support.

Context
128K
tokens
Input
$2.50
per MTok
Output
$10.00
per MTok

Modalities

Input
Text Documents / PDFs Code
Output
Text Code

Code Examples

curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "command-r-plus-08-2024",
    "messages": [
      { "role": "user", "content": "Explain quantum entanglement in one sentence." }
    ]
  }'

API Parameters

Name Type Description
frequency_penalty number Penalize tokens by their frequency so far. Positive values reduce repetition.
max_completion_tokens integer Maximum number of tokens the model may generate in the response.
presence_penalty number Penalize tokens that have appeared at all so far. Positive values encourage new topics.
response_format one of Constrain output to a JSON schema or an enum (structured outputs).
seed integer Deterministic seed for sampling. Same seed + same prompt produces identical output.
stop array Up to 4 sequences where the API will stop generating tokens.
stream boolean Stream partial responses as Server-Sent Events.
temperature number Sampling temperature; higher values produce more random output. 0 is deterministic.
tool_choice one of Controls which (if any) tool is called: "none", "auto", "required", or a specific tool.
tools array List of tools (functions) the model may call.
top_p number Nucleus sampling: consider only tokens whose cumulative probability ≥ top_p.

Standard OpenAI-compatible parameters. Consult the provider docs for model-specific behaviour.

Benchmark Scores

Benchmark Score
MMLU 75.7%
HumanEval 61.6%

Performance

50
tok / sec
output speed

Source: Cohere docs + OpenRouter, April 2026

Strengths & Limitations

Best For
Best-in-class RAG with grounded citations
Multi-step tool use
Strong multilingual support (10+ languages)
Enterprise-focused reliability
Limitations
4K max output tokens
Weaker on pure reasoning vs frontier models
No vision modality

Tags

RAGEnterpriseMultilingualLong ContextTool Use