#modeleval

Live, measured metrics for the hashtag #modeleval from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

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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.

$51.02/ year · 9-character #name
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1
Uses / 7 days
Mastodon
1
Accounts / 7 days
Mastodon
4
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 4
0
Avg reactions / post
Mastodon · last 4

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 07:49 UTC
0
07-21
0
07-22
0
07-23
1
07-24
0
07-25
0
07-26
0
07-27

1 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 2026-07-27 07:49 UTC
#modelevals
1 uses · 1 accounts / 7d
#ModelEvaluation
10 uses · 5 accounts / 7d

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 07:49 UTC

Everything below is measured over the latest 4 public posts (spanning ~9911 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (4)

Avg boosts / post: 0.3

Top of the latest posts

  • How do you validate an LLM benchmark when the judges are also LLMs? 🧐 It’s a fair question. Transparency matters. Our latest installment (#6 of 11) details the architecture to prevent model collusion: multi-judge consensus, exclusion, bias

    llm-bench@KAPUALabs@[email protected]♥ 0↻ 12026-07-24 17:00 UTCView post →

  • How do you validate an LLM benchmark when the judges are also LLMs? 🧐 It’s a fair question. Transparency matters. Our latest installment (#6 of 11) details the architecture to prevent model collusion: multi-judge consensus, exclusion, bias

    llm-bench@KAPUALabs@[email protected]♥ 0↻ 02026-06-29 09:50 UTCView post →

  • Simon Willison (@simonw) OpenAI Codex를 사용해 모델 종류와 추론 강도 조합마다 펠리컨 이미지를 렌더링해본 실험 기록입니다. 작성자는 gpt-5.4의 xhigh(매우 높은 추론력) 변형이 가장 우수한 결과를 냈다고 평가하며, 결과물에 물고기를 물고 있는 펠리컨이 포함되는 등 생성 품질을 관찰했습니다. https://x.com/simonw/status/2033992486096670733 #openai

    ainews@[email protected]♥ 0↻ 02026-03-17 23:52 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/modeleval