BestHub
Sign in
Tagged articles

ARC-AGI-3

6 articles · Page 1 of 1
Machine Heart
Machine Heart
Aug 7, 2026 · Artificial Intelligence

Prime Agent’s RLM Harness Beats ARC‑AGI‑3 but Sparks Controversy

Prime Agent, an open‑source agent framework, claims a 95.5% score on ARC‑AGI‑3 by engineering the RLM harness and a Continual Harness for self‑improvement and long‑running tasks, yet critics question the depth of its recursion, potential reward‑hacking, and whether the benchmark results reflect genuine general intelligence.

ARC-AGI-3Agent FrameworkPrime Agent
0 likes · 14 min read
Prime Agent’s RLM Harness Beats ARC‑AGI‑3 but Sparks Controversy
Machine Heart
Machine Heart
Jul 30, 2026 · Artificial Intelligence

How Two Settings Tripled GPT‑5.6 Sol’s ARC‑AGI‑3 Score

OpenAI found that enabling retained reasoning and context compression in the GPT‑5.6 Sol API raised its ARC‑AGI‑3 benchmark score from 13.3% to 38.3%—a three‑fold increase—while also cutting token usage by about six times, highlighting how evaluation frameworks and settings can mask a model’s true capabilities.

AI benchmarkingARC-AGI-3GPT-5.6
0 likes · 8 min read
How Two Settings Tripled GPT‑5.6 Sol’s ARC‑AGI‑3 Score
Machine Heart
Machine Heart
Jul 18, 2026 · Artificial Intelligence

How the [schema] Harness Achieved 99% RHAE on ARC‑AGI‑3 by Making AI Think Like a Physicist

The article explains how the [schema] harness, a lightweight framework that wraps large language models, transformed ARC‑AGI‑3 scores from sub‑10% to 98.98% by grounding observations into state representations, discovering mechanisms, and iteratively testing hypotheses, while also discussing the benchmark’s scoring rules, potential “cheating” concerns, and the broader implications for AI research.

AI benchmarkingARC-AGI-3LLM
0 likes · 14 min read
How the [schema] Harness Achieved 99% RHAE on ARC‑AGI‑3 by Making AI Think Like a Physicist
Machine Heart
Machine Heart
May 2, 2026 · Artificial Intelligence

Why GPT‑5.5 and Claude Opus 4.7 Score Below 1% on ARC‑AGI‑3 While Humans Achieve 100%

The ARC‑AGI‑3 benchmark shows that GPT‑5.5 (0.43%) and Claude Opus 4.7 (0.18%) fail to solve any of the 135 novel environments, whereas a six‑year‑old human solves them all, and the analysis attributes the gap to three concrete failure modes and differing compression abilities of the two models.

AI BenchmarkARC-AGI-3Claude Opus 4.7
0 likes · 10 min read
Why GPT‑5.5 and Claude Opus 4.7 Score Below 1% on ARC‑AGI‑3 While Humans Achieve 100%