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AMD tests five speculative decoding methods for vLLM on Instinct MI300X and MI355X GPUs

AMD published results from experiments running speculative decoding in vLLM on its MI300X and MI355X Instinct GPUs using the ROCm software stack. The team compared five drafting approaches—native MTP, Gemma 4 MTP, EAGLE-3, DFlash, and DSpark—which differ in how draft tokens are generated and how they receive signals from the target model.

vLLM tool-parser bug let AI-generated text trigger code execution

Researchers documented that vLLM's XML-based tool parser for Qwen3 Coder (CVE-2025-9141) fed model-generated arguments directly into Python's eval() function, meaning a language model's own output tokens could execute arbitrary code on the machine running it. A Gemini-based review flagged the change as a critical risk before it was merged, but the lead vLLM maintainer force-merged it anyway.