#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.

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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
11
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 11
0
Avg reactions / post
Mastodon · last 11

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 11:14 UTC
0
07-21
0
07-22
0
07-23
0
07-24
0
07-25
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07-26
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07-27

0 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 11:14 UTC

No related tags with measured usage found for #distributedinference.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 11:14 UTC

Everything below is measured over the latest 11 public posts (spanning ~10222 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (11)

Avg boosts / post: 0

Top of the latest posts

  • Michael (@michaelharrigan) Arvis의 이미지 생성 기능을 Exo Labs 기반 클러스터에서 구동한 사례다. exolabs/FLUX.1-schnell-4bit 모델을 클러스터의 단일 노드에서 실행했으며, 모델 파라미터와 생성 예시를 함께 공유했다고 밝혔다. 경량 양자화 이미지 모델의 분산/로컬 인프라 운용 참고 사례다. https://x.com/michaelharrigan/status/20788621389

    ainews@[email protected]♥ 0↻ 02026-07-20 11:50 UTCView post →

  • Henry Mascot (@iAmHenryMascot) EXO의 여러 노드가 하나의 머신처럼 동작하며, 경우에 따라 llama.ccp의 RPC를 이용한 다른 추론 방식도 시도할 수 있다고 답합니다. 분산 추론/멀티 디바이스 실행에 대한 실무적 힌트가 담겨 있습니다. https://x.com/iAmHenryMascot/status/2071507889416548824 #distributedinference #llm #rpc #ex

    ainews@[email protected]♥ 0↻ 02026-06-29 10:44 UTCView post →

  • TonoKen3Local-LLM&Robotとのけん3 (@Tono_Ken3) EXO처럼 별도 노드의 PC들에서 분산 추론을 수행할 수 있는 프레임워크가 등장했다는 언급입니다. 로컬/분산 환경에서 LLM 추론을 구성하려는 개발자에게는 흥미로운 소식이지만, 구체적 릴리스 정보나 성능 근거는 없어 중요도는 중간 수준입니다. https://x.com/Tono_Ken3/status/2068489763792040348 #distribute

    ainews@[email protected]♥ 0↻ 02026-06-21 09:48 UTCView post →

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