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# Introduction to torch.compile and How It Works with vLLM

**[vLLM](https://daily.dev/sources/vllm)** · 13 min read · 0 upvotes · 0 comments

## Summary

torch.compile is PyTorch's just-in-time compiler that automatically generates optimized kernels for faster model execution without manual optimization. vLLM integrates torch.compile by default, using compilation caching, dynamic batch size support, and piecewise CUDA Graphs to improve LLM inference performance. The integration includes custom compiler passes for operations like SiLU+quantization fusion and sequence parallelism, achieving performance improvements of 8-15% in various scenarios. Future work focuses on improving stability, reducing startup times, and enhancing custom pass mechanisms.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.vllm.ai/2025/08/20/torch-compile.html>

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---

Tags: [#ai-inference](https://daily.dev/tags/ai-inference), [#compiler-optimization](https://daily.dev/tags/compiler-optimization), [#cuda](https://daily.dev/tags/cuda), [#pytorch](https://daily.dev/tags/pytorch), [#vllm](https://daily.dev/tags/vllm)

[View this post on daily.dev](https://daily.dev/posts/introduction-to-torch-compile-and-how-it-works-with-vllm-1mzylcxhp)

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