Long-Horizon Terminal Bench
PulseAugur coverage of Long-Horizon Terminal Bench — every cluster mentioning Long-Horizon Terminal Bench across labs, papers, and developer communities, ranked by signal.
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New framework generates 37,000 AI agent tasks for $0.05 each
Researchers have developed Recursive Synthetic Terminal Tasks (RST), a framework designed to generate long-horizon training data for terminal agents at a significantly reduced cost. This method recursively synthesizes n…
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AI model evaluations need richer toolkits beyond simple scores
Current AI model evaluation methods, primarily relying on benchmarks, are insufficient for accurately assessing both capabilities and safety. These benchmarks suffer from issues like saturation, unreliability, and gamea…
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Grok 4.5 claims top spot on Long-Horizon Terminal-Bench, beating Claude and GPT models
Grok 4.5 has achieved the top position on the Long-Horizon Terminal-Bench, surpassing Claude Fable 5, Claude Opus 4.8, and GPT-5.6-sol. This ranking was determined by a strict binary pass rate, where a task was only con…
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MiniMax M3 ranks 7th on Long-Horizon Terminal-Bench, open-weight version leads
MiniMax AI's M3 model has achieved the seventh position on the Long-Horizon Terminal-Bench, a benchmark designed to evaluate model performance on extended tasks. Additionally, an open-weight version of the model secured…