On September 22, 2026, Hugging Face added native GGUF support to Transformers, the llama.cpp quantized format behind Ollama, LM Studio, and Jan. If you run local models on Apple Silicon from Python, adopt `from_pretrained` with a GGUF file and drop the homegrown conversions.
On August 20, 2026, Liquid AI released DSpark draft models for its LFM2.5 family, with throughput gains of up to 3.18x on GPU and 2.87x on-device and no change to the output. Teams serving open LLMs in production now have a concrete reason to reprice their cost per token.
Ollama, vLLM, and llama.cpp cover every local inference scenario, from a developer laptop to a GPU cluster. This guide compares real-world throughput, VRAM requirements, and the cost of each approach — so you know which one to deploy by the end of the day.
