Unverified50% confidenceBenchmarkExact time
On the Base models, CopyLoop achieved decoding speedups of 2.98x to 10.70x compared with full-depth autoregressive decoding.
1
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50%
Confidence
Long-term
Relevance
10/30/2026
First Seen
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Related Claims
VerifiedDuring the autoregressive decoding phase, GPU compute utilization is often less than 10%, making it a memory-intensive operation.69% similarUnverifiedFine-tuning on a few hundred real data samples on top of synthetic pre-training can often improve mAP by 10 to 20 percentage points.69% similarUnverifiedDuring the Decode phase of large models, because each step depends on the result of the previous step and can only be executed serially, hardware utilization is typically below 10%.68% similarUnverifiedSpeculative decoding technology makes the speed approximately 1.6 to 1.8 times faster, and in actual tests the large model accepted the small assistant's guesses approximately 79% of the time68% similarVerifiedWhen the draft model prediction accuracy of Speculative Decoding reaches 60–80%, the overall inference speed can be improved by 2–3 times.68% similar
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