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GLM-5.2 speculative decode runs on 4x DGX GB10 cluster

A user successfully implemented GLM-5.2 with MTP speculative decoding on a 4x DGX GB10 cluster, achieving approximately 9.4 tokens/second. This involved reconstructing missing build modifications from public kernels and ensuring the use of a specific vLLM reference commit to avoid weight loading errors. The user also detailed steps for optimizing the setup, including a data-free pruning method to fit the model into memory and notes on network configuration for multi-node performance. AI

IMPACT Demonstrates advanced deployment techniques for large models on specialized hardware, potentially improving inference speeds for users with similar setups.

RANK_REASON User-level integration and optimization of an existing model and framework, not a frontier release or significant industry event.

Read on r/LocalLLaMA →

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

GLM-5.2 speculative decode runs on 4x DGX GB10 cluster

COVERAGE [1]

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

    Got GLM-5.2 + MTP speculative decode running on 4× DGX Spark (GB10) — and the build piece the public recipe is missing

    <!-- SC_OFF --><div class="md"><p>TL;DR: the recipe's image-build mods aren't actually public – I reconstructed them from the public kernels (with Claude) – and you have to build vLLM at the author's exact pinned ref or the real AWQ weights crash on load. Running now at ~9.4 tok/…