Muse Glimmer: New Language Model for Autonomous Tasks Released
Muse Glimmer, a 30-billion-parameter causal language model, has been released, designed for autonomous agentic tasks on consumer hardware. Developed from Muse Spark, the model integrates multi-step reasoning, reliable tool use, multimodal understanding, and failure recovery. It operates locally without requiring cloud infrastructure, making it accessible for a wide range of applications. Muse Glimmer has demonstrated strong performance on various benchmarks, including DeepSearch QA and SWE-Bench, showcasing its ability to handle complex workflows and tool invocations. The model is available through Ollama's MLX engine, initially supporting Apple Silicon, with plans to expand to other platforms.