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ThunderAgent boosts GPU throughput for AI agents, accepted to ICML 2026

By PulseAugur Editorial · [10 sources] ·

Together has developed ThunderAgent, a scheduler-level solution designed to optimize GPU usage for agentic inference by mitigating KV cache thrashing. This innovation leads to a 2.5x increase in single-node throughput and a tenfold reduction in P50 latency under high concurrency. ThunderAgent has been accepted as a Spotlight paper at ICML 2026 and is already being adopted by projects like Skyrlos and NVIDIA Dynamo, offering a drop-in integration for existing engine configurations. AI

IMPACT Optimizes GPU utilization for AI agents, potentially lowering inference costs and improving performance.

RANK_REASON Research paper accepted to a major ML conference detailing a novel technical solution.

Read on X — Runway (video gen) →

AI-generated summary · Google Gemini · from 10 sources. How we write summaries →

ThunderAgent boosts GPU throughput for AI agents, accepted to ICML 2026

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Research
Research paper accepted to a major ML conference detailing a novel technical solution.
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10 independent sources
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infra, product
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45 days old
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COVERAGE [10]

  1. X — SemiAnalysis TIER_1 English(EN) · SemiAnalysis_ ·

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  2. X — Together (inference / OSS) TIER_1 Dansk(DA) · togethercompute ·

    Blog: https://t.co/QXB4QCPxUv

    Blog: https://t.co/QXB4QCPxUv GitHub: https://t.co/SjxnGsUqKE Paper: https://t.co/7I1Yf5s8B8

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