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DeepSeek VL2 vs Gemma 2 9B
Comprehensive side-by-side LLM comparison
Gemma 2 9B leads with 1.4% higher average benchmark score. DeepSeek VL2 supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek VL2 is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 70.9% across 14 benchmarks. It excels particularly in DocVQA (93.3%), ChartQA (86.0%), TextVQA (84.2%). It supports a 259K token context window for handling large documents. 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 2024, it represents DeepSeek's latest advancement in AI technology.
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Gemma 2 9B is a language model developed by Google. It achieves strong performance with an average score of 64.6% across 16 benchmarks. It excels particularly in ARC-E (88.0%), BoolQ (84.2%), HellaSwag (81.9%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Google's latest advancement in AI technology.
5 months newer
Gemma 2 9B
2024-06-27
DeepSeek VL2
DeepSeek
2024-12-13
Performance Metrics
Context window and performance specifications
Average performance across 30 common benchmarks
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DeepSeek VL2
Average Score:33.1%
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Gemma 2 9B
Average Score:34.5%(+1.4%)
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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Gemma 2 9B
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DeepSeek VL2
Avg Score:33.1%
Providers:1
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Gemma 2 9B
Avg Score:34.5%(+1.4%)
Providers:0