A developer confirmed that GLM-5.2, a 753B-parameter DeepSeek-Sparse-Attention MoE model, runs on 8x A100 80GB GPUs using vLLM PR #38476, which adds a Triton sparse-MLA backend for Ampere architecture…
Rudrite Research compares three methods for shrinking large language models: AWQ scales salient weights, GPTQ compensates rounding with second-order math, and BitNet trains ternary weights to turn mat…
Local AI users are accumulating hundreds of gigabytes of model files, including multiple quantizations of the same model, image and video generation weights, and RAG datasets, often with duplicates th…
GGUF, GPTQ, and AWQ are the three dominant formats for running quantized large language models locally, each optimized for different hardware and use cases. GGUF, the format used by llama.cpp and its …
KVBoost is a new open-source Python library that accelerates HuggingFace LLM inference by implementing chunk-level KV cache reuse, achieving 3–5× faster time-to-first-token (TTFT) and up to 85% cache …