Unverified50% confidenceFactExact time
The Talus model was trained from scratch on a single RTX 5060 (8 GB VRAM), accumulating approximately 4.5 hours of training across multiple versions.
1
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50%
Confidence
Long-term
Relevance
10/9/2026
First Seen
Sources
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Unverified在一块消费级RTX 4060显卡上，仅需约24分钟、150万步训练，即可达到100%的任务成功率72% similarUnverifiedDRAFT training requires only approximately 10–12 minutes to complete on an RTX 4090, tested at 512×512 resolution with a batch size of 1 and 12 sampling steps.70% similarUnverifiedThe policy was trained from scratch using mjlab (a wrapper for MuJoCo) and converged in approximately 4 hours on a single RTX 3080.67% similarUnverifiedIn testing on an RTX 5080, the BF16 baseline took approximately 4.651 seconds per sample, while the selective FP8 approach took approximately 3.651 seconds, a speedup of approximately 22%.66% similarUnverifiedRunning 2,048 parallel environments for 25 million steps on a GTX 1050 Ti takes only 2.5 hours of wall-clock time, whereas single-process nes-py would require approximately 52 hours, yielding a speedup of nearly 20×.65% similar
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