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Command R+ vs Qwen3 14B

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 14B.

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 14B

Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...

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Technical Specifications

SpecificationCommand R+Qwen3 14B
ProviderCohereAlibaba
Context Window128,000 tokens131,702 tokens
Agent Suitability86/100N/A
Time to First Token (TTFT)350 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-04-042025-04-28

API Pricing Comparison

Input Price per Million Tokens

Command R+

$2.50

Qwen3 14B

$0.10

Output Price per Million Tokens

Command R+

$10.00

Qwen3 14B

$0.24

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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 14B
HumanEvalPython coding & logic synthesis
7800.0%vsN/A
Command R+
Qwen3 14B
MATHComplex mathematical problem solving
6200.0%vsN/A
Command R+
Qwen3 14B
GPQAGraduate-level expert reasoning
4200.0%vsN/A
Command R+
Qwen3 14B
HellaSwagCommonsense reasoning and inference
8250.0%vsN/A
Command R+
Qwen3 14B
MT-BenchMulti-turn conversation flow quality
800.0%vsN/A
Command R+
Qwen3 14B

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 14B Quirks & Gotchas

No developer gotchas reported.