SGLang

Why it's ranked here

Apache 2.0 licensing and a pip-installable package keep adoption low friction. The routing layer treats several inference engines, not just its own, as pluggable backends, and splits health checking, circuit breaking, worker registry management and cluster discovery into separate modules rather than one monolith. That is the profile of a project built to sit in front of a mixed fleet of engines, not to showcase a single one, and that breadth is what separates a gateway from a narrower serving wrapper.

What's good

The gateway component works as a genuine multi-engine router: its backend selector explicitly lists rival engines alongside its own, and features like circuit breaking, prefix aware load balancing, and split prefill and decode routing are exposed as first class command line flags rather than buried config. The Python side is careful about import order, deliberately claiming shared cache directories before heavier libraries load, and about platform gaps, installing compatibility shims on hardware its main path was not written for.

Tradeoffs

The router's core interface defines many endpoints as optional, defaulting to a not-implemented response unless a specific implementation overrides them, so parity across chat, completions, embeddings, classification, and rerank is not guaranteed everywhere the router runs. The Python package also pulls in a heavy dependency chain, torch among them, and layers several optional backend clients on top, which raises the cost of even a minimal install compared to a thin client library.

How to use it well

This fits teams already running a mix of inference engines across machines who want one front door with load balancing, health checks and prefill and decode splitting handled outside application code, reached through the command line or cluster discovery. It also suits Python developers who want to script multi-turn generation logic directly, with constrained choices and function calls, against a chosen backend. It is not the right pick for someone who wants a single lightweight client with no router or torch dependency at all.

Observed

License

Licensed under the Apache License 2.0.

Packaging

Distributed as a Python package registered on PyPI, installable via pip, alongside a separate Rust crate that builds a standalone router binary.

Interfaces

Includes a Python library (a domain language for chained generation calls), a Python command line tool with serve, generate and version subcommands, and a Rust command line router aliased smg, amg or sglang-router.

Router design

The router's backend selector treats sglang, vllm, trtllm, openai and anthropic as equivalent backend targets rather than assuming its own engine.

Router trait

The router's core trait declares chat completion routing as the only required method; completion, embedding, classification, rerank and response endpoints default to a not-implemented response unless a specific router overrides them.

Platform support

Documented hardware platform support spans NVIDIA and AMD GPUs, Intel Xeon CPUs, Google TPU, Ascend NPU and Moore Threads MUSA accelerators.

Serving features

Prefill-decode disaggregated serving and Kubernetes-based service discovery are built-in router configuration flags, not separate add-ons.

Attribution

The Python package's model loading module is adapted directly from vLLM's model loader, under compatible Apache-2.0 attribution.