Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 3.1% higher average benchmark score. DeepSeek VL2 offers 2.6K more tokens in context window than Llama 3.2 90B Instruct. Llama 3.2 90B Instruct is $4808.75 cheaper per million tokens. Llama 3.2 90B Instruct is available on 5 providers. Both models have their strengths depending on your specific coding needs.
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.
Meta
Llama 3.2 90B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.3% across 13 benchmarks. It excels particularly in AI2D (92.3%), DocVQA (90.1%), MGSM (86.9%). It supports a 256K token context window for handling large documents. The model is available through 5 API providers. 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 2024, it represents Meta's latest advancement in AI technology.
2 months newer
Llama 3.2 90B Instruct
Meta
2024-09-25
DeepSeek VL2
DeepSeek
2024-12-13
Cost per million tokens (USD)
DeepSeek VL2
Llama 3.2 90B Instruct
Context window and performance specifications
Average performance across 21 common benchmarks
DeepSeek VL2
Llama 3.2 90B Instruct
Available providers and their performance metrics
DeepSeek VL2
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Llama 3.2 90B Instruct
DeepSeek VL2
Llama 3.2 90B Instruct
DeepSeek VL2
Llama 3.2 90B Instruct
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