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Weekly benchmark review: 2026-06-22 #63

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Weekly benchmark review (2026-06-22)

Automated check from scripts/weekly-benchmarks-check.mjs. Triage and either:

  • Update data/benchmarks.json if a new flagship model dropped this week, then close this issue, OR
  • Comment noop and close if nothing actionable surfaced.

Current state of data/benchmarks.json

  • lastUpdated: 2026-06-11 (11 days ago)

  • Models tracked: 20

  • Benchmarks tracked: 5

  • Models released within last 60 days: 2

    • 2026-06 | Anthropic | Claude Fable 5
    • 2026-05 | Anthropic | Claude Opus 4.8

Model-release-flavored news, last 7 days

Matched 7 articles (keyword scan; not all will be real releases).

Date Source Title
2026-06-22 Hacker News AI Show HN: Open-source job search plugin for Claude Code
2026-06-22 WIRED AI OpenAI Launches Full-Scale Effort to Patch Open-Source Bugs as It Takes on Anthropic’s Mythos
2026-06-22 Hacker News AI A public Sentry key is all it takes to hijack Claude Code, Cursor, and Codex
2026-06-22 NVIDIA AI Blog From Materials Simulation to Experimental Astronomy, New NVIDIA AI Software Unlocks Scientific Discoveries
2026-06-19 MIT Technology Review A startup claims it broke through a bottleneck that’s holding back LLMs
2026-06-18 WIRED AI The White House Is Making Up Its Rules for AI in Real Time
2026-06-18 The Verge AI Adobe’s redesigned AI studio remembers what your creations look like

Sources: Hacker News AI (2), WIRED AI (2), NVIDIA AI Blog (1), MIT Technology Review (1), The Verge AI (1)

HF Open LLM Leaderboard top 10

Captured: 2026-06-22

Rank Model
1 MaziyarPanahi_calme-3.2-instruct-78b_bfloat16 (avg 52.08 · 78B)
2 MaziyarPanahi_calme-3.1-instruct-78b_bfloat16 (avg 51.29 · 78B)
3 dfurman_CalmeRys-78B-Orpo-v0.1_bfloat16 (avg 51.23 · 78B)
4 MaziyarPanahi_calme-2.4-rys-78b_bfloat16 (avg 50.77 · 78B)
5 huihui-ai_Qwen2.5-72B-Instruct-abliterated_bfloat16 (avg 48.11 · 73B)
6 Qwen_Qwen2.5-72B-Instruct_bfloat16 (avg 47.98 · 73B)
7 MaziyarPanahi_calme-2.1-qwen2.5-72b_bfloat16 (avg 47.86 · 73B)
8 newsbang_Homer-v1.0-Qwen2.5-72B_bfloat16 (avg 47.46 · 73B)
9 ehristoforu_qwen2.5-test-32b-it_bfloat16 (avg 47.37 · 33B)
10 Saxo_Linkbricks-Horizon-AI-Avengers-V1-32B_bfloat16 (avg 47.34 · 33B)

What "needs update" usually means

  1. A flagship from Anthropic / OpenAI / Google / Meta / Mistral / DeepSeek / xAI launched this week → add a row to data/benchmarks.json.
  2. A tracked model has materially-shifted benchmark scores (re-running, methodology change) → update the row.
  3. A new benchmark itself (e.g. a successor to MMLU-Pro) is becoming canonical → add it.

What it usually does NOT mean

  • Research papers about benchmarks (those land on /research, not /benchmarks).
  • HN opinion threads about a model.
  • Pricing-only changes (those go in data/pricing.json).

Bump lastUpdated in data/benchmarks.json whenever you change anything else in the file.

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