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Command R+ vs DeepSeek VL2 Small
Comprehensive side-by-side LLM comparison
DeepSeek VL2 Small leads with 26.3% higher average benchmark score. DeepSeek VL2 Small supports multimodal inputs. Command R+ is available on 2 providers. Overall, DeepSeek VL2 Small 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 VL2 Small is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 69.6% across 14 benchmarks. It excels particularly in DocVQA (92.3%), ChartQA (84.5%), OCRBench (83.4%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
3 months newer
Command R+
Cohere
2024-08-30
DeepSeek VL2 Small
DeepSeek
2024-12-13
Performance Metrics
Context window and performance specifications
Average performance across 20 common benchmarks
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Command R+
Average Score:22.4%
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DeepSeek VL2 Small
Average Score:48.7%(+26.3%)
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:22.4%
Providers:2
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DeepSeek VL2 Small
Avg Score:48.7%(+26.3%)
Providers:0