What is SGLang?
SGLang is a high-performance serving framework for large language and multimodal models. It provides scalable, low-latency inference with high throughput across deployments from a single GPU to distributed clusters.
The engine supports a wide range of open models and diverse hardware platforms, enabling unified model and hardware flexibility.
Runtime optimizations include disaggregated prefill/decode, speculative decoding, parallelism strategies, a zero‑overhead scheduler, and optimized GPU kernels to reduce latency and increase throughput. Deployment is available via pip or Docker and exposes OpenAI-compatible API endpoints for integration.
The project includes tooling for multi-node scaling, monitoring, and community-driven extensions via GitHub and discussion channels.
SGLang pricing
FreeThis tool is free to use, with no credit card required.
Verify on the official pricing page.
Get started freeSGLang's key features
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Serving framework for large language and multimodal models
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Scalable inference from a single GPU to distributed clusters
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Unified support for a wide range of open models and diverse hardware platforms
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Runtime optimizations: disaggregated prefill/decode, speculative decoding, parallelism strategies, zero-overhead scheduler, and optimized GPU kernels
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Deployable via pip or Docker with OpenAI-compatible API endpoints and multi-node scaling/monitoring tooling
SGLang use cases
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Deploy a production-grade, low-latency conversational AI or customer support assistant using SGLang's OpenAI-compatible API endpoints and runtime optimizations—run on a single GPU or scale to multi-node clusters via pip or Docker for real-time responses and high throughput
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Serve multimodal applications like visual search, image captioning, or document understanding by leveraging SGLang's multimodal model serving and distributed GPU serving to process image+text inference at scale with minimal latency
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Build cost-effective batch and streaming inference pipelines for personalization, recommendation, or analytics by deploying SGLang across multi-node clusters, using speculative decoding and other optimizations to maximize throughput and reduce inference latency while keeping integration simple
SGLang user reviews
Based on 3 reviews, 100% of users recommend SGLang, rated highly for quality results.
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Main competitors of SGLang
Here are some of the major competitors comparisons vs. SGLang.
Who is SGLang for?
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Machine learning engineers
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Mlops engineers
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Infrastructure/platform engineers
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Devops engineers
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Ai/ml researchers
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Data scientists deploying production models
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Startups building llm- or multimodal-powered apps
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Enterprise engineering teams
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Cloud service providers and sres
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Gpu/cluster administrators
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Software engineers integrating models via openai-compatible apis
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Open-source contributors and community developers
SGLang FAQ
Is SGLang free?
Yes. SGLang is free to use and does not require a credit card.
What are the best alternatives to SGLang?
The closest alternatives to SGLang are Vllm, SiliconFlow, Wafer AI, liteLLM and LLMAPI.ai. You can compare them side by side in the alternatives section further down this page.
