Tool overview
SGLang is listed under AI Infrastructure & MLOps AI tools.
What is SGLang?
SGLang is an Apache-2.0 serving framework for large language, multimodal, embedding, classification, and diffusion models. It provides OpenAI-compatible APIs, advanced scheduling, parallelism, caching, and deployment across modern GPU infrastructure.
Best for
Engineering teams serving high-throughput language and multimodal models
Who is it for?
Decision note
Rebuilt from the original export under the complete V411 factual-source-verification workflow. Preview only. Apply remains blocked until Failures = 0, Warnings = 0, Unmapped = 0, Missing = 0; explicit clears are reviewed; image import is disabled or V380 accepts the asset; a representative WordPress edit screen is compared with the export and proposed row; and a post-Apply zero-change Preview succeeds.
Key features
OpenAI-compatible model serving APIs
Advanced scheduling, caching, and parallelism
Language, multimodal, embedding, and diffusion workloads
Docker, Kubernetes, cloud, and on-premises deployment
Use cases
Serve production LLM endpoints
Deploy multimodal models
Optimize throughput and latency
Run distributed inference fleets
Pros
- Apache-2.0 open source
- Actively maintained production releases
- Broad hardware and cloud adoption
Cons
- Requires substantial infrastructure expertise
- Operational cost comes from compute and storage
Limitations
Performance depends on hardware, model architecture, kernels, quantization, and deployment topology.
Operators must secure endpoints, isolate tenants, validate model licenses, and monitor resource exhaustion.
Pricing details
Billing options
Pricing note
The SGLang software is free under Apache-2.0. Users pay for their own GPU, cloud, networking, storage, and operations.
Supported languages
- English
Integrations
OpenAI-compatible clients
Kubernetes
Slurm
AWS
Azure
Google Cloud
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