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Command A vs Command R+

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Command A and Command R+.

Cohere

Command A

Command A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases. Compared to other leading proprietary...

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Cohere

Command R+

Cohere's enterprise-optimized model built for advanced Retrieval-Augmented Generation (RAG) and multi-step tool use. Highly effective for multilingual business processes.

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Technical Specifications

SpecificationCommand ACommand R+
ProviderCohereCohere
Context Window256,000 tokens128,000 tokens
Agent SuitabilityN/A86/100
Time to First Token (TTFT)N/A350 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-03-132024-04-04

API Pricing Comparison

Input Price per Million Tokens

Command A

$2.50

Command R+

$2.50

Output Price per Million Tokens

Command A

$10.00

Command R+

$10.00

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
N/Avs7570.0%
Command A
Command R+
HumanEvalPython coding & logic synthesis
N/Avs7800.0%
Command A
Command R+
MATHComplex mathematical problem solving
N/Avs6200.0%
Command A
Command R+
GPQAGraduate-level expert reasoning
N/Avs4200.0%
Command A
Command R+
HellaSwagCommonsense reasoning and inference
N/Avs8250.0%
Command A
Command R+
MT-BenchMulti-turn conversation flow quality
N/Avs800.0%
Command A
Command R+

Command A Quirks & Gotchas

No developer gotchas reported.

Command R+ Quirks & Gotchas

  • โ–ธOptimized for RAG workflows โ€” best enterprise document search model
  • โ–ธTool calling requires explicit step definitions in Cohere's tool-use format