AutoRound

A forum thread is crowdsourcing real-world local LLM deployment data across five VRAM tiers — ≤16GB, 24–32GB, 48–64GB, 96–128GB, and 196–256GB+ — asking users to report model, quantization (AutoRound …

Archsloth published a September 14th correction to its AutoRound quantization workflow, reporting that two changed settings produced a Qwen3-4B GGUF file with 20.9% to 54.4% lower KL divergence than U…

Intel's AutoRound quantization algorithm for large language models claims state-of-the-art performance, enabling LLMs like Qwen 3.6 to run on consumer GPUs. In testing, AutoRound produced consistent o…