ATLAS: Adaptive Learning System for Faster LLM Inference Without Manual Tuning
By
alecco
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Summary
Together AI introduces ATLAS (AdapTive-LeArning Speculator System), a novel runtime-learning accelerator for LLM inference that automatically improves performance without manual tuning. The system adapts continuously to workloads, achieving 500 TPS on DeepSeek-V3.1 with a 4x speedup over baseline performance. ATLAS represents a new paradigm in speculative decoding where models get faster with use through continuous adaptation to specific inference patterns.
Key quotes
· 4 pulledATLAS offers a new way of doing speculative decoding — LLM inference that gets faster as you use it
Our runtime-learning accelerator adapts continuously to your workload, delivering 500 TPS on DeepSeek-V3.1
4x speedup over baseline performance without manual tuning
Making large language models faster, cheaper, and more efficient is not a one-trick problem — it requires optimizing along multiple axes
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