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Command R+ vs DeepSeek-V3.1
Comprehensive side-by-side LLM comparison
DeepSeek-V3.1 leads with 22.1% higher average benchmark score. DeepSeek-V3.1 offers 71.7K more tokens in context window than Command R+. Both models have similar pricing. Overall, DeepSeek-V3.1 is the stronger choice for coding tasks.
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Cohere
Command R+ is a language model developed by Cohere. It achieves strong performance with an average score of 74.6% across 6 benchmarks. It excels particularly in HellaSwag (88.6%), Winogrande (85.4%), MMLU (75.7%). It supports a 256K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents Cohere's latest advancement in AI technology.
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DeepSeek
DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). It supports a 328K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
4 months newer
Command R+
Cohere
2024-08-30
DeepSeek-V3.1
DeepSeek
2025-01-10
Pricing Comparison
Cost per million tokens (USD)
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Command R+
Input:$0.25
Output:$1.00($0.02 cheaper)
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DeepSeek-V3.1
Input:$0.27
Output:$1.00
Performance Metrics
Context window and performance specifications
Average performance across 22 common benchmarks
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Command R+
Average Score:20.3%
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DeepSeek-V3.1
Average Score:42.5%(+22.1%)
Provider Availability & Performance
Available providers and their performance metrics
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Command R+
2 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Cohere
Throughput: 59 tok/s
Latency: 0.65ms
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Command R+
Avg Score:20.3%
Providers:2
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DeepSeek-V3.1
Avg Score:42.5%(+22.1%)
Providers:2