AnalysisOpinion / analysisEfficiency & Inference1 source · Oct 22, 2026

2-bit copy in VRAM + exact residual in system RAM as the verifier: speculative decoding for models that don't fit your GPU

Not sure if it is outdated or not, it can work also with MTP.

Proof1 community thread

Key points

  • Keep a 2-bit version of the model on the GPU and the rest of the weights (the residual, 6-8 bit) in system RAM.
  • The 2-bit copy drafts tokens, then the full model checks them: the GPU does the 2-bit part, the CPU does the residual part, and only activations go over PCIe.
  • the 2-bit draft that reuses the verifier's KV cache gets 25-30% more accepted tokens per check than Google's official Gemma 4 drafter (31B, 16 node tree: 5.23 vs 4.20)
  • Closest thing I found is SubSpec, but it uses a separate 4-bit copy and streams weights over PCIe instead of splitting the model by bits.

Sources (1)

Extractive summary: sentences quoted from the sources.

Before this

  1. Oct 21, 2026Recursive shows first result of its AI-driven research process with Flint
  2. Oct 21, 2026Granite Speech 5.0: Transcribe, Translate, and Attribute more Accurately and Faster
  3. Oct 21, 2026Google Cloud Ships llm-d 1.0 With Cache-Aware Routing for TPU and GPU Fleets
  4. Oct 20, 2026Gradium Open-Sources Phonon, a 31M-Parameter On-Device TTS Model Under Apache 2.0
  5. Oct 20, 2026[AINews] DeepSeek DeepInfer: Open Source SOTA Inference running 155T toks/day/cluster making $22m/day at ~80% margin for a 81 day payback
  6. Oct 20, 2026MPS in PyTorch 2.15

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