Meta 发布 Muse Glimmer：30B 参数本地部署
LFG: Meta’s Muse Glimmer is a remarkably capable model for its size: 30B paramet…
做 Agent 和本地部署的同学注意了，Muse Glimmer 在多项 Agent 基准上超过 Qwen，且 4-bit 仅 17GB，赶紧试试能不能替换你现在的模型。
LFG: Meta’s Muse Glimmer is a remarkably capable model for its size: 30B parameters, local deployment, and the best reported result on 12 of 24 benchmark rows against Gemma4-31B and Qwen3.6-27B.
By my count, it beats Gemma on 19 of 24 rows and Qwen on 14.
Its strongest area is agentic work:
-MCP Atlas: 75.5 vs. Qwen’s 62.5
-DeepSearch QA: 74.6 vs. 71.1
-τ³-Banking: 23.5 vs. 16.7
-SWE-Bench Pro: 51.2 vs. 50.2
-AA-LCR: 80.0 vs. 73.3
Qwen remains ahead on OSWorld, TerminalBench and most multimodal tests. Gemma leads the two primary safety metrics.
The 4-bit model fits into roughly 17GB with only 1% average degradation across 15 benchmarks, according to Meta.
And this is an unusually open Meta release: public, ungated weights under Apache 2.0, including BF16 and quantized versions, the perception encoder and DFlash drafter.
Meta delivered! Really excited for this one!
更进一步：量化金融体系
看懂新闻只是起点——沿量化金融路径，把它变成能交付的工程能力