#modelsize
Live, measured metrics for the hashtag #modelsize from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #modelsize
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 2026-09-13 16:48 UTC1 uses by 1 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 2026-09-13 16:48 UTCLive pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-09-13 16:48 UTCEverything below is measured over the latest 8 public posts (spanning ~5535 hours).
Posting hours (UTC)
Languages: English (7) · Spanish (1)
Avg boosts / post: 0
Top of the latest posts
@poleguy Curioso cómo los límites de VRAM marcan la diferencia. Con 12 GB puedes probar modelos de 4 B y menos, pero la velocidad cae. Los modelos de 7 B empiezan a requerir 20 GB+ para un batch de 1. Si buscas rendimiento, mira versiones o
Serio_ai (@Multi_Serio_Ai) 컴퓨팅 자원이 있다면 31B 모델을 더 높은 수준으로 양자화해 쓰는 것이 좋고, 26B는 간혹 이상한 출력이 나온다는 실무 팁이다. 모델 크기와 양자화 설정이 품질에 미치는 영향을 직접적으로 언급한다. https://x.com/Multi_Serio_Ai/status/2071945260545273989 #quantization #llm #inference #modelsize
GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2 최근 대형 AI 모델들이 무조건 크기만 키우는 것이 능사가 아니라는 논의가 부상하고 있습니다. MIT 라이선스의 오픈소스 GLM-5.2(753B 파라미터)는 GPT-5.5(1-2T 파라미터 추정)보다 훨씬 적은 환각률(28% vs 86%)을 기록하며, 크기 대비 실제 지능과 정확도가 크게 향상될 수 있음을 보여줍니다. 대형 모델들
#modelsize across platforms
every network with a public tag surfaceFollow #modelsize 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/modelsize