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Command R+ vs Qwen3 VL 235B A22B Thinking

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 VL 235B A22B Thinking.

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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Alibaba

Qwen3 VL 235B A22B Thinking

Qwen3-VL-235B-A22B Thinking is a multimodal model that unifies strong text generation with visual understanding across images and video. The Thinking model is optimized for multimodal reasoning in STEM and math....

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Technical Specifications

SpecificationCommand R+Qwen3 VL 235B A22B Thinking
ProviderCohereAlibaba
Context Window128,000 tokens131,072 tokens
Agent Suitability86/100N/A
Time to First Token (TTFT)350 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-04-042025-09-23

API Pricing Comparison

Input Price per Million Tokens

Command R+

$2.50

Qwen3 VL 235B A22B Thinking

$0.26

Output Price per Million Tokens

Command R+

$10.00

Qwen3 VL 235B A22B Thinking

$2.60

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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
7570.0%vsN/A
Command R+
Qwen3 VL 235B A22B Thinking
HumanEvalPython coding & logic synthesis
7800.0%vsN/A
Command R+
Qwen3 VL 235B A22B Thinking
MATHComplex mathematical problem solving
6200.0%vsN/A
Command R+
Qwen3 VL 235B A22B Thinking
GPQAGraduate-level expert reasoning
4200.0%vsN/A
Command R+
Qwen3 VL 235B A22B Thinking
HellaSwagCommonsense reasoning and inference
8250.0%vsN/A
Command R+
Qwen3 VL 235B A22B Thinking
MT-BenchMulti-turn conversation flow quality
800.0%vsN/A
Command R+
Qwen3 VL 235B A22B Thinking

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

Qwen3 VL 235B A22B Thinking Quirks & Gotchas

No developer gotchas reported.