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DeepSeek VL2 vs Kimi K2-Instruct-0905
Comprehensive side-by-side LLM comparison
Kimi K2-Instruct-0905 leads with 20.1% higher average benchmark score. DeepSeek VL2 supports multimodal inputs. Overall, Kimi K2-Instruct-0905 is the stronger choice for coding tasks.
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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-Instruct-0905 is a language model developed by Moonshot AI. It achieves strong performance with an average score of 64.1% across 29 benchmarks. It excels particularly in MATH-500 (97.4%), MMLU-Redux (92.7%), IFEval (89.8%). 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.
8 months newer
DeepSeek VL2
DeepSeek
2024-12-13
Kimi K2-Instruct-0905
Moonshot AI
2025-09-05
Performance Metrics
Context window and performance specifications
Average performance across 43 common benchmarks
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DeepSeek VL2
Average Score:23.1%
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Kimi K2-Instruct-0905
Average Score:43.2%(+20.1%)
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-Instruct-0905
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DeepSeek VL2
Avg Score:23.1%
Providers:1
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Kimi K2-Instruct-0905
Avg Score:43.2%(+20.1%)
Providers:0