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Command R+ vs DeepSeek-V3
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 35.8% higher average benchmark score. DeepSeek-V3 offers 6.1K more tokens in context window than Command R+. Both models have similar pricing. Overall, DeepSeek-V3 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 is a language model developed by DeepSeek. It achieves strong performance with an average score of 67.2% across 20 benchmarks. It excels particularly in DROP (91.6%), CLUEWSC (90.9%), MATH-500 (90.2%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
3 months newer
Command R+
Cohere
2024-08-30
DeepSeek-V3
DeepSeek
2024-12-25
Pricing Comparison
Cost per million tokens (USD)
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Command R+
Input:$0.25
Output:$1.00($0.12 cheaper)
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DeepSeek-V3
Input:$0.27
Output:$1.10
Performance Metrics
Context window and performance specifications
Average performance across 25 common benchmarks
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Command R+
Average Score:17.9%
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DeepSeek-V3
Average Score:53.7%(+35.8%)
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:17.9%
Providers:2
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DeepSeek-V3
Avg Score:53.7%(+35.8%)
Providers:1