#smalllanguagemodels
Live, measured metrics for the hashtag #smalllanguagemodels from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #smalllanguagemodels
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 2026-08-07 07:17 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 2026-08-07 07:17 UTCNo related tags with measured usage found for #smalllanguagemodels.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-08-07 07:17 UTCEverything below is measured over the latest 39 public posts (spanning ~21575 hours).
Posting hours (UTC) — busiest: 18:00
Languages: English (37) · Norwegian (1)
Avg boosts / post: 0.2
Top of the latest posts
Key Points: ➡️ SLMs with 1-8B parameters can perform as well or better than LLMs. ➡️ SLMs are task-agnostic or task-specific. ➡️ SLMs balance performance, efficiency, scalability, and cost. ➡️ SLMs are effective in resource-constrained envi
🤖 🗣️ Small language models are more reliable and secure than their large counterparts, primarily because they draw information from a circumscribed dataset. Expect to see more chatbots running on these slimmed-down alternatives in the com
Microsoft Research (@MSFTResearch) SocialRL로 소형 언어 모델의 협상 능력을 학습시키는 연구, 아프리카 언어권 음성 AI 평가 범위를 넓힌 PazaBench V2, 에이전트가 경험을 재사용 가능한 지식으로 전환하도록 돕는 EvoLib를 소개했다. 또한 신뢰도 높은 A/B 테스트 방법과 AI 기반 정밀 종양학 연구 진전도 함께 다룬 AI 연구 동향 요약이다. https://x.com/MSFTRe
#smalllanguagemodels across platforms
every network with a public tag surfaceFollow #smalllanguagemodels 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/smalllanguagemodels