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DeepSeek V4 Flash runs on single RTX 6000 Pro with vLLM-Moet

A developer has successfully run the DeepSeek V4 Flash model on a single RTX 6000 Pro GPU, utilizing a customized version of vLLM called vLLM-Moet. This setup allows for a 130K context window, though it requires approximately 150 GB of RAM for initial loading before fitting into the GPU's VRAM. The key to this achievement is the compression of routed experts to 2-bit while retaining fp4 experts, a technique attributed to the vLLM-Moet developer. AI

IMPACT Demonstrates efficient deployment of large models on consumer-grade hardware, potentially lowering barriers to entry for advanced AI research.

RANK_REASON User-driven optimization and benchmark of an existing model, not a new release from a frontier lab. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

DeepSeek V4 Flash runs on single RTX 6000 Pro with vLLM-Moet

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/live4evrr ·

    Deepseek V4 Flash on a single RTX 6000 Pro - vLLM-Moet

    <!-- SC_OFF --><div class="md"><p>Wow...</p> <p><a href="https://github.com/kacper-daftcode/vLLM-Moet">https://github.com/kacper-daftcode/vLLM-Moet</a></p> <p>Using this customized vllm provided as a docker, I'm able to run DS V4 Flash on a single RTX 6000 Pro (apparently it also…