#SGLang
Live, measured metrics for the hashtag #SGLang from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #sglang
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 · mastodon.social (Mastodon public tags API) · fetched 2026-07-27 21:00 UTC2 uses by 2 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.social (Mastodon public search API) · fetched 2026-07-27 21:00 UTCLive pulse
measured · mastodon.social (Mastodon tag timeline) · fetched 2026-07-27 21:00 UTCEverything below is measured over the latest 29 public posts (spanning ~10893 hours).
Posting hours (UTC) — busiest: 10:00
Languages: English (21) · German (4) · Russian (3) · Chinese (Taiwan) (1)
Avg boosts / post: 0.4
Top of the latest posts
SGLang vừa giải quyết ổn định FP8 cho huấn luyện RL, phát hiện vấn đề nằm ở bước lượng tử hóa (quantization step). Đây là bước tiến lớn cho RLHF và tinh chỉnh RL cục bộ, giúp đơn giản hóa việc sử dụng độ chính xác hỗn hợp. #SGLang #FP8 #RLT
Install SGLang with uv, pip, or Docker; configure YAML and server flags; then serve Hugging Face LLMs with an OpenAI-compatible API plus native /generate and offline Engine examples. #Cheatsheet #Self-Hosting #LLM #AI #AI Coding #DevOps #Do
RT @ZenMagnets: Minimax m2.7 nvfp4 läuft mit ~130 tok/s im Single-Stream auf 2x RTX 6k mit sglang. Bis zu ~1500 tok/s bei 64 gleichzeitigen frischen Kontexten. Enormer Leistungsabfall bei höheren Kontexten. Aber viel schneller als meine m2.
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/sglang