{"database": "staticevolution", "table": "blog_quotation", "rows": [[7, "2026-08-11 02:02:32.095104+00:00", "introducing-muse-glimmer", null, null, "Introducing Muse Glimmer\n\nMeta are back in the open weights game! Muse Glimmer is a brand new 30B model under a clean Apache 2.0 license (a step up from the janky Llama licenses of old).\nThey claim to have optimized it for exactly the kind of things I'm looking for in a local model:\n\nEnd-to-end Agentic Task Completion. Muse\u00a0Glimmer achieves strong success rates on full-task benchmarks including DeepSearch QA, MCP-Atlas, \ud835\uded5-Bench and SWE-Bench, which measure its ability to work within scaffolds, write and debug code, and resolve multi-turn requests from start to finish.\nReliable Tool Use. The model handles a wide range of function calls, invoking tools with precise schemas throughout extended workflows.\nMulti-Step Reasoning. Muse\u00a0Glimmer chains reasoning over long horizons, sustaining coherent plans across complex, extended workflows. [...]", "Introducing Muse Glimmer - Simon Willison", "https://simonwillison.net/2026/Aug/10/introducing-muse-glimmer/#atom-everything", "Need to try this one. "]], "columns": ["id", "created", "slug", "card_image", "series_id", "quotation", "source", "source_url", "context"], "primary_keys": ["id"], "primary_key_values": ["7"], "units": {}, "query_ms": 0.47045573592185974}