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Command R vs Qwen 2.5-Coder 32B

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 Qwen 2.5-Coder 32B.

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

Qwen 2.5-Coder 32B

Qwen 2.5-Coder 32B is Alibaba's specialized code generation model built on the Qwen 2.5 architecture, fine-tuned on a massive corpus of code repositories, technical documentation, and programming discussions. It achieves competitive results against GPT-4o and Claude Sonnet on coding benchmarks like HumanEval, MBPP, and LiveCodeBench while supporting a broad range of programming languages from Python and JavaScript to Rust and Go. Its 128K context window enables whole-repository analysis and complex multi-file refactoring tasks.

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Technical Specifications

SpecificationCommand RQwen 2.5-Coder 32B
ProviderCohereAlibaba
Context Window128,000 tokens131,072 tokens
Agent Suitability78/10089/100
Time to First Token (TTFT)200 ms260 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-03-112025-11-12

API Pricing Comparison

Input Price per Million Tokens

Command R

$0.15

Qwen 2.5-Coder 32B

$0.35

Output Price per Million Tokens

Command R

$0.60

Qwen 2.5-Coder 32B

$0.70

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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
Qwen 2.5-Coder 32B
HumanEvalPython coding & logic synthesis
7300.0%vsN/A
Command R
Qwen 2.5-Coder 32B
MATHComplex mathematical problem solving
5400.0%vsN/A
Command R
Qwen 2.5-Coder 32B
GPQAGraduate-level expert reasoning
3500.0%vsN/A
Command R
Qwen 2.5-Coder 32B
HellaSwagCommonsense reasoning and inference
7800.0%vsN/A
Command R
Qwen 2.5-Coder 32B
MT-BenchMulti-turn conversation flow quality
750.0%vsN/A
Command R
Qwen 2.5-Coder 32B

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

Qwen 2.5-Coder 32B Quirks & Gotchas

  • โ–ธStrong code generation across 40+ languages โ€” excellent for multi-language repos
  • โ–ธAvailable via Alibaba Cloud API or self-hosted