A 125B model can run quickly on a gaming PC when the system treats the GPU, RAM, CPU, and SSD as one memory hierarchy. This guide explains the Strata setup, quantization, expert caching, and speculative decoding behind fast Qwen3.8-Flash-Next inference.
Magnitude is an open-source inference engine built for local AI agents. It profiles your hardware, selects models that fit, and tunes kernels, caching, and memory use for the machine running them.
Jeff turns Qwen3.5 and Gemma 4 into small decision models that classify plain-language situations without generating a paragraph. The 0.8B version reports probabilities in roughly 22–28 ms on listed GPU and Apple silicon hardware, while local fine-tuning can adapt it to specialized tasks.
Muse Glimmer is Meta’s open-weight 30B agentic model released under Apache 2.0, designed to run locally for coding and tool-using workflows. Its local feasibility comes from quantization for memory fit and DFlash-based speculative decoding for faster generation.