#distributedinference
Live, measured metrics for the hashtag #distributedinference from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #distributedinference
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.online (Mastodon public tags API) · fetched 2026-10-21 12:34 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-10-21 12:34 UTCNo related tags with measured usage found for #distributedinference.
Live pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-10-21 12:34 UTCEverything below is measured over the latest 20 public posts (spanning ~12103 hours).
Posting hours (UTC) — busiest: 03:00
Languages: English (20)
Avg boosts / post: 0
Top of the latest posts
AI✖️Satoshi⏩️ (@AiXsatoshi) 약 7,530억 파라미터(활성 400억), 464GB 규모의 GLM-5.3 NVFP4 모델을 PC 2대와 RTX PRO 6000 GPU 8장으로 구동해 47.65 tok/s를 기록했다. 4 GPU×2노드, TP4·PP2 구성과 10GbE 노드 간 연결 조건이며, MTP·오버랩 스케줄·Radix Cache 없이 측정한 대규모 분산 추론 사례다. https://x.com/AiXsa
Sudo su (@sudoingX) DGX Spark 36대를 연결해 총 4.6TB 규모의 통합 메모리를 구성하는 사례를 언급했다. 작성자는 24대가 이미 가동 중이며, 대형 오픈 모델을 풀 프리시전으로 올릴 수 있는 용량이라고 주장한다. 소규모 노드 다수로 대형 모델을 운용하는 개인·랩 단위 AI 인프라 구성 사례다. https://x.com/sudoingX/status/2103892354264391829 #gpu #aiin
Matt Mireles (@mattmireles) Apple Silicon에서 Kokoro TTS 추론을 직접 최적화해 빠른 구현체를 만들었으며, 현재 Whisper 사후학습(post-training)을 진행 중이라고 밝혔다. Mac 4대와 iPad 2대로 개인용 분산 추론 네트워크도 운영 중이며, 향후 관련 결과물을 오픈소스로 공개할 계획이다. https://x.com/mattmireles/status/209245599571
#distributedinference across platforms
every network with a public tag surfaceFollow #distributedinference 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/distributedinference