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zhyncs merged 1 commit into from
Jul 7, 2025
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docs: update README #7821

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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -65,7 +65,7 @@ Learn more in the release blogs: [v0.2 blog](https://lmsys.org/blog/2024-07-25-s
[Development Roadmap (2025 H1)](https://github.com/sgl-project/sglang/issues/4042)

## Adoption and Sponsorship
SGLang has been deployed at large scale, generating trillions of tokens in production every day. It is trusted and adopted by a broad range of leading enterprises and institutions, including xAI, NVIDIA, AMD, Google Cloud, Oracle Cloud, LinkedIn, Cursor, Voltage Park, Atlas Cloud, DataCrunch, Baseten, Nebius, Novita, InnoMatrix, RunPod, Stanford, UC Berkeley, UCLA, ETCHED, Jam & Tea Studios, Hyperbolic, as well as major technology organizations across North America and Asia. As an open-source LLM inference engine, SGLang has become the de facto standard in the industry, with production deployments running on over 100,000 GPUs worldwide.
SGLang has been deployed at large scale, generating trillions of tokens in production each day. It is trusted and adopted by a wide range of leading enterprises and institutions, including xAI, AMD, NVIDIA, Intel, LinkedIn, Cursor, Oracle Cloud, Google Cloud, Microsoft Azure, AWS, Atlas Cloud, Voltage Park, Nebius, DataCrunch, Novita, InnoMatrix, MIT, UCLA, the University of Washington, Stanford, UC Berkeley, Tsinghua University, Jam & Tea Studios, Baseten, and other major technology organizations across North America and Asia. As an open-source LLM inference engine, SGLang has become the de facto industry standard, with deployments running on over 1,000,000 GPUs worldwide.
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The list of adopting enterprises and institutions is getting quite long. To improve readability and make it easier to maintain in the future, consider sorting the list alphabetically. This makes it easier for readers to find a specific name and for future contributors to add new entries in the correct place.

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SGLang has been deployed at large scale, generating trillions of tokens in production each day. It is trusted and adopted by a wide range of leading enterprises and institutions, including xAI, AMD, NVIDIA, Intel, LinkedIn, Cursor, Oracle Cloud, Google Cloud, Microsoft Azure, AWS, Atlas Cloud, Voltage Park, Nebius, DataCrunch, Novita, InnoMatrix, MIT, UCLA, the University of Washington, Stanford, UC Berkeley, Tsinghua University, Jam & Tea Studios, Baseten, and other major technology organizations across North America and Asia. As an open-source LLM inference engine, SGLang has become the de facto industry standard, with deployments running on over 1,000,000 GPUs worldwide.
SGLang has been deployed at large scale, generating trillions of tokens in production each day. It is trusted and adopted by a wide range of leading enterprises and institutions, including AMD, Atlas Cloud, AWS, Baseten, Cursor, DataCrunch, Google Cloud, InnoMatrix, Intel, Jam & Tea Studios, LinkedIn, Microsoft Azure, MIT, Nebius, Novita, NVIDIA, Oracle Cloud, Stanford, Tsinghua University, UC Berkeley, UCLA, the University of Washington, Voltage Park, xAI, and other major technology organizations across North America and Asia. As an open-source LLM inference engine, SGLang has become the de facto industry standard, with deployments running on over 1,000,000 GPUs worldwide.


<img src="https://raw.githubusercontent.com/sgl-project/sgl-learning-materials/refs/heads/main/slides/adoption.png" alt="logo" width="800" margin="10px"></img>

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