#swebench

Live, measured metrics for the hashtag #swebench 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 #swebench

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.

$110.68/ year · 8-character #name
Claim #swebench — $110.68/yr→
Annual, renews each year
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one-timepay once, yours for life
card via hashtag.org · tokens via hashtag.space
1
Uses / 7 days
Mastodon
1
Accounts / 7 days
Mastodon
40
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 40
0.1
Avg reactions / post
Mastodon · last 40

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 02:25 UTC
0
07-21
1
07-22
0
07-23
0
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 02:25 UTC
#swebenchpro
0 uses · 0 accounts / 7d
#swebench_pro
0 uses · 0 accounts / 7d
#swebench_verified
0 uses · 0 accounts / 7d
#swebenchlite
0 uses · 0 accounts / 7d
#swebench_verified_benchmark
0 uses · 0 accounts / 7d
#swebenchdrama
0 uses · 0 accounts / 7d
#swebenchpassers
0 uses · 0 accounts / 7d
#swebenchmark
0 uses · 0 accounts / 7d

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 02:25 UTC

Everything below is measured over the latest 40 public posts (spanning ~10222 hours).

Posting hours (UTC) — busiest: 14:00

00:0012:0023:00

Languages: English (27) · Russian (8) · Portuguese (2) · Korean (2)

Avg boosts / post: 0.3

Top of the latest posts

  • If your company is benefiting from Django’s stability and maturity to test or train AI models, consider **funding Django’s development**. 💚 Support Django: https://www.djangoproject.com/fundraising/ #Django #AI #LLM #Benchmarks #OpenSource

    Jeff Triplett@[email protected]♥ 4↻ 62025-09-26 14:18 UTCView post →

  • How does it perform? Empirically, on the scenarios I’ve tested (including hand-picked #SWEbench Lite & Multilingual tasks), access to an #ORF playbook cut agent step counts roughly in half (~50%) and eliminated error loops.

    Guillaume Laforge@[email protected]♥ 0↻ 02026-07-22 14:44 UTCView post →

  • Daniel Han (@danielhanchen) Codex의 GPT-5.6-Sol xhigh가 Margin Lab의 일일 SWE Bench Pro에서 성능이 크게 상승해, 50개 랜덤 문제 기준 약 82%를 기록했다고 합니다. 직전 5.5 Xhigh의 약 54%보다 개선 폭이 커서, Codex 기반 코드 생성/리뷰 품질 향상 신호로 볼 수 있습니다. https://x.com/danielhanchen/status/2076304

    ainews@[email protected]♥ 0↻ 02026-07-12 21:45 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/swebench