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NInfer engine achieves 542 tok/s for Qwen3.6 on single RTX 5090

A new inference engine called NInfer, built from scratch in C++/CUDA, has been open-sourced, demonstrating impressive performance with the Qwen3.6-35B-A3B model. The engine achieved a sustained speed of 542 tokens per second for a full 65,536 token completion on a single RTX 5090 GPU. This optimization was achieved through custom quantization, kernel fusion, and other deep pipeline enhancements, making NInfer highly specialized for specific Qwen3.6 checkpoints. AI

IMPACT Optimized inference engines like NInfer can significantly boost the performance and accessibility of large language models on consumer hardware.

RANK_REASON The cluster describes the release of an open-source inference engine and its performance benchmarks with a specific model, which falls under research and development in AI infrastructure. [lever_c_demoted from research: ic=1 ai=1.0]

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

NInfer engine achieves 542 tok/s for Qwen3.6 on single RTX 5090

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/FormOne2615 ·

    543 tok/s single-request Qwen3.6-35B-A3B on one RTX 5090 over a 65K-token decode

    <!-- SC_OFF --><div class="md"><p><a href="https://reddit.com/link/1v1no8e/video/k5zlxk2ideeh1/player">An example</a></p> <h1>TL;DR</h1> <p>I have open-sourced <a href="https://github.com/Neroued/ninfer">NInfer</a>, a from-scratch C++/CUDA inference engine currently specialized f…