Run DeepSeek R1 on Just 480GB of VRAM

DeepSeek R1 remains a leading open-source LLM despite the emergence of closed models like Grok and Sonnet 3.7, offering a transparent alternative for those concerned about data privacy in closed platforms. Hosting DeepSeek R1 has been simplified by quantization, allowing a Q4 4-bit version to run on platforms like Runpod, making it accessible for $10 to $16 per hour depending on the hardware configuration, with deployment achievable in approximately 20 minutes. DeepSeek has also contributed to the AI community by open-sourcing five repositories during Open Source Week, addressing key performance bottlenecks in LLM deployment and inference, such as variable-length sequence handling through FlashMLA, communication overhead in Mixture of Experts models with DeepEP, and matrix multiplication efficiency via DeepGEMM. Additionally, they have introduced optimized parallelism strategies with DualPipe and EPLB, and advanced storage solutions with the Fire-Flyer File System (3FS), which significantly improves data handling efficiency in large-scale AI models. These developments not only enhance the performance of DeepSeek R1 but also pave the way for future innovations in the AI infrastructure landscape.