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AI 1 min read

Optimizing Qwen 3.5 on PyTorch Achieves Record-Breaking 580 Tokens/Second 🚀

The PyTorch Foundation has announced TokenSpeed optimization for Qwen 3.5, achieving speeds of 580 tokens per second on NVIDIA GPUs and unlocking ultra-fast processing for agentic workflows.

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The PyTorch Foundation and the community have reached a major milestone in optimizing inference performance for the Qwen 3.5 model family. Powered by the TokenSpeed engine, processing speeds have hit a record-breaking 580 tokens per second (tps) on NVIDIA GPUs.

Key Developments

This "speed of light" optimization focuses on handling agentic workloads, where AI agents require ultra-fast responses to execute continuous sequences of actions. A community blog post from the PyTorch Foundation details how TokenSpeed maximizes hardware architecture to achieve this record performance for Qwen 3.5.

Why It Matters

Inference speed is critical for complex agent applications that must think and respond in an instant. Achieving 580 tps shows that Qwen 3.5 on PyTorch infrastructure is ready for large-scale tasks, significantly reducing latency and operational costs for enterprises deploying AI agents on NVIDIA GPUs.