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DeepSeek VL2 vs Gemma 3n E4B
Comprehensive side-by-side LLM comparison
. 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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Gemma 3N E4B was developed as a slightly larger edge-optimized variant, designed to provide enhanced capabilities while still fitting within edge computing constraints. Built to serve applications that can accommodate more parameters for improved quality, it expands the range of edge deployment options.
6 months newer
DeepSeek VL2
DeepSeek
2024-12-13
Gemma 3n E4B
2025-06-26
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Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
Gemma 3n E4B
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
1 providers
Replicate
Throughput: 22 tok/s
Latency: 0.5ms
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Gemma 3n E4B
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DeepSeek VL2
Avg Score:0.0%
Providers:1
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Gemma 3n E4B
Avg Score:0.0%
Providers:0