#模型量化
Live, measured metrics for the hashtag #模型量化 from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #模型量化
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-08-23 05:59 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-08-23 05:59 UTCNo related tags with measured usage found for #模型量化.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-08-23 05:59 UTCEverything below is measured over the latest 5 public posts (spanning ~2523 hours).
Posting hours (UTC)
Languages: Chinese (Taiwan) (5)
Avg boosts / post: 0
Top of the latest posts
🌕 Qwen/Qwen3.8-27B-FP8 · Hugging Face ➤ 兼顧高效能與低資源消耗的 Qwen3.8-27B-FP8 多模態模型部署指南 ✤ https://huggingface.co/Qwen/Qwen3.8-27B-FP8 本文介紹 Qwen3.8-27B-FP8 模型的技術特點與多種部署實作方法。該模型是基於 Qwen3.5 架構升級的 27B 密集型原生視覺語言模型，採用細粒度 FP8 量化（塊大小 128），在近乎不損失原始效能的前提下顯著降
🌗 Needle 2：專為微型設備打造的 14 MB 智慧代理大型語言模型 ➤ 突破邊緣運算極限，讓 14MB 的超輕量模型賦能百億物聯網設備 ✤ https://cactuscompute.com/needle Cactus 推出僅 14MB 大小的開源智慧代理模型 Needle 2，專為無 GPU、低記憶體的微型物聯網設備與平價手機設計。Needle 2 擁有 4500 萬參數，透過獨創的簡單注意力網路與 2-bit 訓練中量化技術，僅需 28MB 的系統記憶體即可流暢
🌕 隆重介紹 Muse Glimmer：一款可在個人裝置上運行的開源智能體模型 | Meta AI 研究 ➤ 開啟邊緣運算新紀元：在本地端流暢執行複雜 AI 智能體任務 ✤ https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model Meta AI 研究團隊推出了 Muse Glimmer，這是一款擁有 300 億參數、專為本地端智能體工作流設計的開源模型。開發團隊透過創新的對數機率蒸餾
#模型量化 across platforms
every network with a public tag surfaceFollow #模型量化 straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/模型量化