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DeepSeek VL2 vs Gemini 2.0 Flash Thinking
Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash Thinking leads with 24.3% higher average benchmark score. Overall, Gemini 2.0 Flash Thinking is the stronger choice for coding tasks.
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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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Gemini 2.0 Flash Thinking was developed to incorporate extended reasoning capabilities into the Flash family, designed to combine quick response times with deeper analytical processing. Built to handle tasks requiring both speed and thoughtful problem-solving, it bridges the gap between fast inference and reasoning-enhanced models.
1 month newer
DeepSeek VL2
DeepSeek
2024-12-13
Gemini 2.0 Flash Thinking
2025-01-21
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek VL2
Average Score:51.1%
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Gemini 2.0 Flash Thinking
Average Score:75.4%(+24.3%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash Thinking
2024-08-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
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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Gemini 2.0 Flash Thinking
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DeepSeek VL2
Avg Score:51.1%
Providers:1
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Gemini 2.0 Flash Thinking
Avg Score:75.4%(+24.3%)
Providers:0