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DeepSeek VL2 vs Kimi K2 Base
Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 3.5% 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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Moonshot AI
Kimi K2 Base is a language model developed by Moonshot AI. It achieves strong performance with an average score of 69.2% across 13 benchmarks. It excels particularly in C-Eval (92.5%), GSM8k (92.1%), MMLU-redux-2.0 (90.2%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Moonshot AI's latest advancement in AI technology.
7 months newer
DeepSeek VL2
DeepSeek
2024-12-13
Kimi K2 Base
Moonshot AI
2025-07-11
Performance Metrics
Context window and performance specifications
Average performance across 27 common benchmarks
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DeepSeek VL2
Average Score:36.8%(+3.5%)
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Kimi K2 Base
Average Score:33.3%
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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Kimi K2 Base
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DeepSeek VL2
Avg Score:36.8%(+3.5%)
Providers:1
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Kimi K2 Base
Avg Score:33.3%
Providers:0