LLM Reference

Command R+

Released
2024-04-04
Last refreshed
2026-05-16
Status
Researched 46d ago
RAGLong contextClassificationJSON / Tool use

Command R+ is worth evaluating for rag, long context, and classification when its provider route and context window match the workload.

Use it for

  • Teams evaluating rag, long context, and classification
  • Workloads that can use a 128k context window
  • Buyers comparing 4 tracked provider routes

Do not use it for

  • Vision or document-understanding workloads
Specifications
Family
Command R
Released
2024-04-04
Context
128k
Parameters
104B*
Architecture
Decoder Only
Knowledge cutoff
2023-02
Specialization
general
Training
finetuned
Created by

Empowering developers with advanced language AI.

Toronto, Ontario, Canada
Founded 2022
Website
Pricing
Output / 1M
$10.00
Input / 1M
$2.50

Cheapest of 6 routes · Cohere API

About

Command R+ is a powerful large language model from Cohere, tailored for robust enterprise applications. It features an architecturally impressive 104 billion parameters and a 128k-token context window, allowing it to adeptly manage complex tasks and long dialogue sessions. Its cutting-edge capabilities include retrieval-augmented generation (RAG) with inline citations, multilingual functionality supporting ten major languages, and multi-step tool usage to automate complex workflows. The model is suited for diverse business operations such as financial analysis, customer support, and content creation, and can be accessed via Cohere's API or through platforms like Microsoft Azure and Oracle Cloud Infrastructure. Its deployment is subject to a non-commercial license, though exceptions can be considered.

Command R+ is a model in the Command R family. The structured metadata tracks a 128k-token context window and structured outputs. This page tracks provider routes through Cohere API, AWS Bedrock, Microsoft Foundry, and 3 more, with the cheapest tracked route listed at $2.5 input and $10 output per 1M tokens. Headline tracked benchmarks include Massive Multitask Language Understanding 79.3 and Chatbot Arena 1210.0.

Top use-case fit

RAG

Included by capability and metadata signals in the decision map.

Long context

Included by capability and metadata signals in the decision map.

Classification

Q/$ D

1 relevant benchmark in the decision map.

Provider price ladder

Compare all 6

Compare API pricing across 4 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Cohere API$2.50$10.00
Serverless
OpenRouter$2.50$10.00
Serverless
AWS Bedrock$3.00$15.00
Serverless
Microsoft Foundry$3.00$15.00
Serverless

Capabilities

Structured Outputs

Benchmark peer barsfor Classification

Benchmark scores(2)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionSource
Massive Multitask Language Understanding79.35-shothttps://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard
Chatbot Arena1210.0https://lmarena.ai

Migration checks

No linked migration route is available for this model yet.

Rankings & picks(7)

Comparison and alternatives

Browse all comparisons →