@TheAhmadOsman: Yannick is criminally underfollowed in the Local AI space for the depth of his work

X AI KOLs Timeline Models

Summary

Yannick Nick demonstrates running DeepSeek V4 Flash with native FP4+FP8 precision on 2x RTX Pro 6000 GPUs using KTransformers, enabling efficient inference on resource-constrained systems.

Yannick is criminally underfollowed in the Local AI space for the depth of his work
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Cached at: 06/26/26, 08:15 PM

Yannick is criminally underfollowed in the Local AI space for the depth of his work

Yannick Nick (@keennay):

  • DeepSeek V4 Flash - Native Precision (FP4 + FP8)
  • Fits on 2x RTX Pro 6000 GPUs + 256 GB DDR5 RAM
  • Using KTransformers: KVCache-AI fork of SGLang for GPU/CPU memory inference

I have a somewhat obsession running applications on resource constrained systems to squeeze the

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@danveloper: https://x.com/danveloper/status/2064387956387758206

X AI KOLs Timeline

A developer ran DeepSeek-V4-Flash on a Raspberry Pi 5 by streaming model weights from an NVMe SSD, achieving 1.3 tokens/second at 8 watts, demonstrating the feasibility of frontier-adjacent open-weight models on low-cost, offline hardware.

I have (even faster) DeepSeek V4 Pro at home

Reddit r/LocalLLaMA

A user reports successfully running the DeepSeek V4 Pro model locally using ktransformers and sharing detailed benchmark results across various context depths, demonstrating improved inference speeds.