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DeepSeek VL2 Tiny vs Gemini 2.0 Flash-Lite
Comprehensive side-by-side LLM comparison
DeepSeek VL2 Tiny leads with 4.5% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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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.
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Gemini 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
1 month newer
DeepSeek VL2 Tiny
DeepSeek
2024-12-13
Gemini 2.0 Flash-Lite
2025-02-05
Performance Metrics
Context window and performance specifications
Average performance across 26 common benchmarks
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DeepSeek VL2 Tiny
Average Score:34.0%(+4.5%)
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Gemini 2.0 Flash-Lite
Average Score:29.5%
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash-Lite
2024-06-01
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 Tiny
0 providers
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Gemini 2.0 Flash-Lite
1 providers
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DeepSeek VL2 Tiny
Avg Score:34.0%(+4.5%)
Providers:0
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Gemini 2.0 Flash-Lite
Avg Score:29.5%
Providers:1