Unverified50% confidenceBenchmarkExact time
In the same experiment, the new build's prefill speed is instead about 6.5% slower than the old build (11.14 vs 11.91 tok/s).
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50%
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Long-term
Relevance
10/12/2026
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UnverifiedFew-step generation approaches involve a quality-speed trade-off: with too few steps, the model struggles to correct early errors, which can lead to blurry details or unnatural motion.67% similarUnverifiedIn this task, scaling the model from 7B/8B to 14B yielded only marginal performance gains.67% similarUnverifiedExperiments show that repeating training on the same data for more than 4 epochs yields diminishing performance gains and can sometimes result in slight performance degradation.66% similarUnverifiedWhen training a small DQN on a single environment on CPU, throughput is approximately 400 steps per second and cannot be improved by increasing the number of threads.66% similarUnverifiedIn every round of this experiment, the flat version without architectural constraints consistently took less time overall.66% similar
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