#sparseattention

Live, measured metrics for the hashtag #sparseattention 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
19
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 19
0.1
Avg reactions / post
Mastodon · last 19

Day-by-day usage

measured · mas.to (Mastodon public tags API) · fetched 2026-07-26 22:46 UTC
0
07-20
0
07-21
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · mas.to (Mastodon public search API) · fetched 2026-07-26 22:46 UTC

No related tags with measured usage found for #sparseattention.

Live pulse

measured · mas.to (Mastodon tag timeline) · fetched 2026-07-26 22:46 UTC

Everything below is measured over the latest 19 public posts (spanning ~6157 hours).

Posting hours (UTC) — busiest: 04:00

00:0012:0023:00

Languages: English (16) · German (3)

Avg boosts / post: 0.1

Top of the latest posts

  • #ZAI: #GLM5, a new large language model, is designed for #complexsystemsengineering and long-horizon agentic tasks. It boasts 744 billion parameters and integrates #DeepSeek #SparseAttention for improved efficiency. GLM-5 outperforms previo

    AIagent.at 🤖 AI News@[email protected]♥ 1↻ 02026-02-12 04:08 UTCView post →

  • MiniMax-M3: A native multimodal model with 1M context MiniMax-M3는 1백만 토큰 컨텍스트를 지원하는 4280억 파라미터 규모의 네이티브 멀티모달 모델로, 텍스트, 이미지, 비디오를 처음부터 혼합 모달리티로 학습해 깊은 의미 융합을 이룬다. MiniMax Sparse Attention(MSA) 기법을 도입해 긴 컨텍스트에서의 연산 효율과 메모리 사용량을 크게 개선했으며, 기존 모

    ainews@[email protected]♥ 0↻ 02026-06-12 23:39 UTCView post →

  • MiniMax (official) (@MiniMax_AI) MiniMax M3 오픈웨이트 모델이 공개되었고, Hugging Face에서 가중치를 확인할 수 있습니다. 또한 MiniMax Sparse Attention 관련 자료도 함께 제공되어 모델 구조를 살펴볼 수 있습니다. https://x.com/MiniMax_AI/status/2065435616297509095 #minimax #huggingface #openweight

    ainews@[email protected]♥ 0↻ 02026-06-12 22:49 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/sparseattention