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Command R vs Qwen3.6 27B

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 R and Qwen3.6 27B.

Cohere

Command R

Command R is Cohere's lightweight, cost-efficient model engineered for high-speed enterprise integrations, productivity automation, and retrieval-augmented generation (RAG) pipelines. Optimized for low-latency API tool use and structured JSON output, it is particularly effective in enterprise search and question-answering systems where fast, reliable responses are critical. With a 128,000-token context window and a price of $0.15/MTok for input, Command R provides strong RAG performance and multilingual support at a fraction of the cost of Command R+, making it the preferred choice for teams scaling intelligent document retrieval at high request volumes.

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Alibaba

Qwen3.6 27B

Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities โ€” accepting text, image, and video inputs...

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Technical Specifications

SpecificationCommand RQwen3.6 27B
ProviderCohereAlibaba
Context Window128,000 tokens262,144 tokens
Agent Suitability78/100N/A
Time to First Token (TTFT)200 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-03-112026-04-27

API Pricing Comparison

Input Price per Million Tokens

Command R

$0.15

Qwen3.6 27B

$0.28

Output Price per Million Tokens

Command R

$0.60

Qwen3.6 27B

$2.40

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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
7100.0%vsN/A
Command R
Qwen3.6 27B
HumanEvalPython coding & logic synthesis
7300.0%vsN/A
Command R
Qwen3.6 27B
MATHComplex mathematical problem solving
5400.0%vsN/A
Command R
Qwen3.6 27B
GPQAGraduate-level expert reasoning
3500.0%vsN/A
Command R
Qwen3.6 27B
HellaSwagCommonsense reasoning and inference
7800.0%vsN/A
Command R
Qwen3.6 27B
MT-BenchMulti-turn conversation flow quality
750.0%vsN/A
Command R
Qwen3.6 27B

Command R Quirks & Gotchas

  • โ–ธCost-effective RAG model โ€” strong multilingual search performance
  • โ–ธLimited agentic capability โ€” use Command R+ for complex multi-step tool use

Qwen3.6 27B Quirks & Gotchas

No developer gotchas reported.