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Command R+ vs DeepSeek VL2 Tiny
Comprehensive side-by-side LLM comparison
DeepSeek VL2 Tiny leads with 21.8% higher average benchmark score. DeepSeek VL2 Tiny supports multimodal inputs. Command R+ is available on 2 providers. Overall, DeepSeek VL2 Tiny 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 Tiny is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 63.1% across 14 benchmarks. It excels particularly in DocVQA (88.9%), ChartQA (81.0%), OCRBench (80.9%). 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 Tiny
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 Tiny
Average Score:44.2%(+21.8%)
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:22.4%
Providers:2
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DeepSeek VL2 Tiny
Avg Score:44.2%(+21.8%)
Providers:0