#ttft
Live, measured metrics for the hashtag #ttft from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #ttft
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 2026-07-27 12:15 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 2026-07-27 12:15 UTCLive pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 12:15 UTCEverything below is measured over the latest 4 public posts (spanning ~3493 hours).
Posting hours (UTC)
Languages: English (3) · Russian (1)
Avg boosts / post: 0
Top of the latest posts
AISatoshi (@AiXsatoshi) GLM5.2-IQ4에서 프리필과 디코드를 분리한 TTFT 이론값을 분석했다. 10GbE와 1GbE 네트워크 차이만으로도 TTFT가 수 초~수십 초 벌어질 수 있으며, KV 캐시를 Q8_0으로 설정하면 차이를 약 절반으로 줄일 수 있다고 제시했다. 10GbE 환경에서는 프리필 담당 컴퓨트가 병목으로 나타났다. https://x.com/AiXsatoshi/status/20774291395
Cколько железа нужно ИИ-агенту? Как мы считали ресурсы для on-premise LLM и почему калькуляторы ошиблись в 5 раз На связи Сергей Смирнов, AI-инженер и основатель LLMStart.ru. Один из самых частых вопросов от бизнеса: «Сколько и какого желез
KVBoost – chunk-level KV cache reuse for HuggingFace, 5–48x faster TTFT https://pythongiant.github.io/KVBoost/ #HackerNews #KVBoost #HuggingFace #AI #Performance #Optimization #CacheReuse #TTFT
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/ttft