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DeepSeek VL2 vs Granite 3.3 8B Instruct
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. 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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IBM
Granite 3.3 8B Instruct is a multimodal language model developed by IBM. It achieves strong performance with an average score of 69.8% across 14 benchmarks. It excels particularly in HumanEval (89.7%), AttaQ (88.5%), HumanEval+ (86.1%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents IBM's latest advancement in AI technology.
4 months newer
DeepSeek VL2
DeepSeek
2024-12-13
Granite 3.3 8B Instruct
IBM
2025-04-16
Performance Metrics
Context window and performance specifications
Average performance across 28 common benchmarks
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DeepSeek VL2
Average Score:35.5%(+0.5%)
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Granite 3.3 8B Instruct
Average Score:34.9%
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Knowledge Cutoff
Training data recency comparison
Granite 3.3 8B Instruct
2024-04-01
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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Granite 3.3 8B Instruct
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DeepSeek VL2
Avg Score:35.5%(+0.5%)
Providers:1
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Granite 3.3 8B Instruct
Avg Score:34.9%
Providers:0