Polyrouter vs SGLang
Polyrouter
polyrouter.appSGLang
sglang.ioSide by side
| Figure | Polyrouter | SGLang |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · LLM gateways | 7.8 (#21) | 8.4 (#11) |
| Spec score · LLM Gateway Software | 7.6 (#22) | 8.1 (#12) |
| Integrations | Provider options include API keys, OAuth subscriptions, compatible custom endpoints, and self-hosted local models including Ollama, LM Studio, and llama.cpp. | The README lists deployment and orchestration integrations including Ray Serve, NVIDIA Dynamo, and llm-d. |
| License | Polyrouter is open source under the AGPL-3.0 license. | The GitHub repository identifies the project license as Apache-2.0. |
| Security | Provider and notification credentials are encrypted at rest, and user-supplied URLs are checked against private and metadata address ranges. | The repository identifies its license as Apache-2.0. |
| Support | The maker directs bug reports, feature requests, and questions to GitHub. | The project points users to GitHub issues, Slack, Discord, and community discussions for questions and help. |
Plans
In their own words
Polyrouter
Polyrouter has no write-up on Specifiction yet; its figures are above.
SGLang
SGLang is a free, open-source inference framework for serving large language, vision-language and diffusion models. It targets agentic workloads, reinforcement-learning rollouts and large-scale serving, from one GPU to distributed clusters. Runtime features include RadixAttention, prefix caching and multi-GPU parallelism. Listed optimizations include disaggregated prefill and decode, speculative decoding, a zero-overhead scheduler and optimized GPU kernels. Supported models include DeepSeek, Qwen, GPT-OSS, Llama, Mistral and GLM. SGLang works with Hugging Face and OpenAI APIs and exposes OpenAI-compatible endpoints. It installs with pip or Docker and supports self-hosted deployment. Hardware support spans NVIDIA and AMD GPUs, Google TPUs, Intel GPUs and CPUs, Apple Silicon, Huawei Ascend NPUs and Moore Threads GPUs. SGLang Diffusion adds image and video generation. The Apache-2.0 license permits open-source use.