
Sixteen LLMs find new TIS-100 score frontiers on 18 of 55 puzzles
Opus 5.5 and GPT-6 Astra each solved all 55; Opus found 72 new frontier points to Astra's 32.
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Opus 5.5 and GPT-6 Astra each solved all 55; Opus found 72 new frontier points to Astra's 32.
Harmony-to-RT-Thread translation averages a 0.1667 pass rate, and executable state-machine code remains weak.
On 50 C/C++ programs, five models’ verifiable success ranged from 23% to 81%, and more information access did not reliably help the hardest cases.
Models were scored on 809 questions and 5,012 rubric criteria covering safety, validity, and personalization.
With scaffolded evidence, the best of eight models reached 44.44% accuracy and 45.07% Macro-F1.
Twelve models score 35.4% pass@1 on NPC items versus 63.8% on paired P twins; extra time barely helps.
Across 28 model configurations, even frontier systems reach at most 22% accuracy in some communities.
Grid-Bench tests whether LLMs can predict full grid states after sequences of spatial operations.
A benchmark finds LLMs can store records in telegraph-style cablese, cutting tokens by up to 49 percent without hurting later answers.
Expert-validated 1,042-item benchmark finds LLMs never exceed 0.45 free-text correctness on Colombian law, with about half of cited legal norms wrong or nonexistent.

DrivingBench trio connected off-the-shelf LLMs to a rented Corolla's controls; only GPT-6 Astra completed their parking-lot cone course.

UN and Google launch UN System Data Commons for AI agents; UNICEF benchmark finds six major LLMs answered global statistics questions with just 21.2% accuracy.
Hobbyist benchmark re-runs the pelican-bicycle SVG test on six 2026 frontier models, comparing generation time and API cost per image.
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