#MLPerf

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

hashtag.org network · sponsored

Own #mlperf

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.

$520.70/ year · 6-character #name
Claim #mlperf — $520.70/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
22
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 22
0.1
Avg reactions / post
Mastodon · last 22
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mas.to (Mastodon public tags API) · fetched 2026-11-07 19:16 UTC
0
11-01
0
11-02
0
11-03
0
11-04
0
11-05
0
11-06
0
11-07

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 2026-11-07 19:16 UTC
#mlperf3
0 uses · 0 accounts / 7d
#mlperfinference60
0 uses · 0 accounts / 7d
#mlperfinferencebenchmarktests
0 uses · 0 accounts / 7d

Live pulse

measured · mas.to (Mastodon tag timeline) · fetched 2026-11-07 19:16 UTC

Everything below is measured over the latest 22 public posts (spanning ~33782 hours).

Posting hours (UTC) — busiest: 15:00

00:0012:0023:00

Languages: English (15) · German (3) · Japanese (2) · Polish (1) · French (1)

Avg boosts / post: 0.1

Top of the latest posts

  • AI-Benchmarks: Nvidia gibt Ausblick auf Rubin, AMD noch keinen auf MI400 https://www.computerbase.de/news/grafikkarten/mlperf-inference-v6-1-intel-xeon-und-arc-lebt-512-mi355x-skalieren-und-vr200-debuetiert.99435/ #MLPerf #Benchmarks

    ComputerBase@[email protected]♥ 1↻ 02026-09-17 05:00 UTCView post →

  • Learning about the value of benchmarks at #AIFD6, including #MLPerf Storage and Client, from David Kanter of #MLCommons Watch live on TechFieldDay.com!

    Stephen Foskett@[email protected]♥ 1↻ 02025-01-29 16:26 UTCView post →

  • NVIDIA Jetson Thor finished MLPerf’s new edge agentic suite 6.4× faster than the reference stack on the same board. The run kept ~96% of prompt tokens in a warm cache. Is long-context reuse now the real edge bottleneck, not peak TOPS? https

    Ryan Daws 🤓@[email protected]♥ 0↻ 12026-09-17 11:13 UTCView post →

#mlperf across platforms

every network with a public tag surface

Follow #mlperf 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.

X (Twitter) ↗Instagram ↗TikTok ↗Facebook ↗LinkedIn ↗YouTube ↗Threads ↗Bluesky ↗Mastodon ↗Reddit ↗Pinterest ↗Tumblr ↗

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/mlperf