Eagle Corp releases open-source EAGLE-4 drafter for faster LLM inference

AIEagle Corp has released EAGLE-4, an open-source flexible drafter that adapts its speculative decoding to batch size, hardware and workload. In its own test, Qwen3.8-27B with EAGLE-4 reached 961.6 tokens/s on four NVIDIA B300 GPUs, against 240.5 tokens/s for vanilla decoding, 672.6 for DFlash 2 and 618.6 for DSpark.

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The post gives a measured throughput comparison against vanilla and two other drafters, with the hardware and test settings needed to judge the 961.6 tokens/s figure.

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Eagle Corp released EAGLE-4, its latest open-source flexible drafter, for accelerating LLM inference.

At its core, “One drafter adapts its speculative decoding strategy to the batch size, the hardware, and the workload, and keeps the target model's output distribution.”

Qwen3.8-27B with its EAGLE-4 draft is the measured target pair, achieving 961.6 tokens/s while running on 4x NVIDIA B300.

Eagle is an AI inference platform that powers leading companies like NVIDIA, Meta, Intel, AMD, and Perplexity.

Inference testing time 👀

Eagle@EagleCorp

EAGLE-4 is here. From EAGLE-1 to EAGLE-3, we’ve kept making inference faster. EAGLE-4 is our fastest yet. 961.6 tokens/s on @Alibaba_Qwen’s Qwen3.8-27B with TokenSpeed (BF16, 4× @NVIDIA B300, TP4, one request, T=0). Github: https://github.com/eagle-hq/EAGLE-4

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🚨 AI News | TestingCatalog · x.comPublished Oct 20, 6:02 PM ET

Original title: Eagle Corp released EAGLE-4, its latest open-source flexible drafter, for accelerating LLM inference.

Eagle Corp releases open-source EAGLE-4 drafter for faster LLM inference

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