Entity trail

Terminal-Bench-Science

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Sources

Corpus findings

2026-08-28 / hn-researcherTerminal-Bench-Science Launches With 70 Researcher-Authored Tasks and No Model Above 30%The v0.1.0 release is a continuous benchmark built from researchers' own workflows: 70 tasks across Life Sciences (19), Physical (17), Mathematical (17), Engineering (9) and Earth Sciences (8), assembled by 376 contributors across 22 countries. Claude Opus 5 leads at 30.0%, followed by GPT-5.6 Sol at 22.4%, Claude Fable 5 at 21.4%, Claude Opus 4.8 at 10.5%, GPT-5.6 Terra at 8.6%, GLM 5.3 at 8.1%, Kimi K3 and Grok 4.6 at 7.1%, and GPT-5.6 Luna at 3.3%. The spread between Opus 5 and Opus 4.8 is nearly 3x, which is a far wider generational gap than the same models show on saturated coding benchmarks.
2026-08-21 / arxiv-researcherTask-CoEvolve Cuts Agent Harness Optimization Cost 80% by Only Evaluating Tasks the Candidates Disagree OnarXiv 2608.20169 attacks the waste in harness optimization, where each iteration re-runs a fixed validation set in full even on tasks that stopped discriminating between candidates. Task-CoEvolve uses variance-weighted sampling driven by past outcomes to concentrate evaluation near the agent's capability frontier, then reweights by sampling probability to estimate full-set scores from partial runs so iterations stay comparable. On online text classification and Terminal-Bench 2.1 it beats fixed-subset baselines and matches full-set search's final performance with 80% fewer evaluations, with code promised at github.com/Agent4Science-UTokyo/Task-CoEvolve.
2026-04-26 / skill-finderOpenAI Launches GPT-5.5 and GPT-5.5 Pro: First Model Classified 'High' Cybersecurity Risk Under Preparedness Framework — $5/M Input, 82.7% Terminal-Bench 2.0OpenAI released GPT-5.5 on April 23 with GPT-5.5 Pro following for API on April 24. This is the first model OpenAI has classified as 'High' under its Preparedness Framework for cybersecurity capabilities. GPT-5.5 scores 82.7% on Terminal-Bench 2.0 for command-line tool use, with Pro showing large gains in business, legal, education, and data science. API pricing: $5/$30 per million tokens (standard), $30/$180 (Pro). Nearly 200 early-access partners tested before release.

Graph relationships

BENCHMARKED AGAINST
GLM-5.3
GLM 5.3 scored 8.1% on Terminal-Bench-Science.
Source finding
BENCHMARKED AGAINST
GPT-5.6 Terra
GPT-5.6 Terra scored 8.6% on Terminal-Bench-Science.
Source finding
BENCHMARKED AGAINST
Claude Opus 4.8
Claude Opus 4.8 scored 10.5% on Terminal-Bench-Science.
Source finding
BENCHMARKED AGAINST
Claude Fable 5
Claude Fable 5 scored 21.4% on Terminal-Bench-Science.
Source finding
BENCHMARKED AGAINST
GPT-5.6 Sol
GPT-5.6 Sol scored 22.4% on Terminal-Bench-Science.
Source finding
BENCHMARKED AGAINST
Claude Opus 5
Claude Opus 5 scored 30.0% on Terminal-Bench-Science.
Source finding
BENCHMARKED AGAINST
GLM-5.3 -> Terminal-Bench-Science
GLM 5.3 scored 8.1% on Terminal-Bench-Science.
Source finding

Source trail

Terminal-Bench-Science / Hacker News arXiv 2608.20169 OpenAI — Introducing GPT-5.5

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