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FreeToken Unlocks Frontier MoE Inference on Consumer Hardware via Dynamic Co-Execution

Researchers from UC Berkeley and MIT have developed FreeToken, an open-source inference engine that enhances the utility of Mixture-of-Experts models on consumer hardware. By implementing a dynamic scheduling policy and optimising weight management, FreeToken improves decoding speeds and execution efficiency in edge AI applications, fostering self-hosted reasoning systems. By Olimpiu Pop

2026-08-29 原文 →
AI 资讯

Meta Open-Sources Muse Glimmer: A 30B Local Agentic Model Optimised for On-Device Execution

Meta AI Research has introduced Muse Glimmer, a 30-billion-parameter open-weight model under the Apache 2.0 license, designed for local workflows. It enables autonomous agents and complex task execution on consumer GPUs without relying on cloud APIs. The model employs a multi-stage training approach for efficient performance and supports multimodal inputs, enhancing coding and automation tasks. By Olimpiu Pop

2026-08-14 原文 →