Tibo (@thsottiaux)
작성자는 최신 조합으로 코딩 성능에서 SoTA를 달성했고, 토큰 효율성(token-efficiency)과 추론 최적화(inference optimizations)를 결합해 지난주 버전보다 빠르다고 주장합니다. 고·극고(reasoning effort) 환경에서 GPT-5.3-Codex가 GPT-5.2-Codex보다 약 60~70% 더 빠르다고 명시합니다.
Tibo (@thsottiaux)
작성자는 최신 조합으로 코딩 성능에서 SoTA를 달성했고, 토큰 효율성(token-efficiency)과 추론 최적화(inference optimizations)를 결합해 지난주 버전보다 빠르다고 주장합니다. 고·극고(reasoning effort) 환경에서 GPT-5.3-Codex가 GPT-5.2-Codex보다 약 60~70% 더 빠르다고 명시합니다.
Chased/acc (@ChaseWang)
Qwen3 30B 모델이 가정 환경에서도 구동되어 초당 약 20 token 처리 속도를 낸다고 보고되었으며, 이 성능은 @exolabs 덕분이라고 언급하고 있습니다.
A Multi-Level, Multi-Scale Comparison Of Lidar- And LANDSAT-Based Habitat Selection Models Of Mexican Spotted Owls In A Post-Fire Landscape
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https://doi.org/10.1016/j.ecoinf.2025.103168 <-- shared paper
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