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DeepSeek VL2 vs DeepSeek VL2 Small
Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 1.3% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-VL2 was developed as a vision-language model, designed to handle both visual and textual inputs for multimodal understanding tasks. Built to extend DeepSeek's capabilities beyond text-only processing, it enables applications requiring integrated analysis of images and language.
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DeepSeek
DeepSeek-VL2-Small was created as a compact vision-language variant, designed to bring multimodal capabilities to applications with limited computational resources. Built to provide visual and textual understanding in a more efficient package, it serves use cases requiring practical deployment of vision-language AI.
Launched on the same date
DeepSeek VL2
DeepSeek
2024-12-13
DeepSeek VL2 Small
DeepSeek
2024-12-13
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Performance Metrics
Context window and performance specifications
Average performance across 14 common benchmarks
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DeepSeek VL2
Average Score:70.9%(+1.3%)
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DeepSeek VL2 Small
Average Score:69.6%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek VL2
1 providers
Replicate
Throughput: 22 tok/s
Latency: 0.5ms
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DeepSeek VL2 Small
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DeepSeek VL2
Avg Score:70.9%(+1.3%)
Providers:1
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DeepSeek VL2 Small
Avg Score:69.6%
Providers:0