Requesty vs SGLang

Requesty is a managed AI gateway that gives applications access to more than 600 models through one API. Its OpenAI-compatible API can work with existing SDK code after changing the base URL and API key. Routing features include policy and regional rules, automatic failover and load balancing. Requesty tracks cost, latency and usage, with analytics by model, user and team. Governance options include PII detection and scrubbing, content guardrails, team roles, model allowlists and audit logs. Named integrations include OpenAI, LangChain, PydanticAI, Vercel AI SDK, Haystack and LlamaIndex TS; the integrations page also lists tools such as Claude Code, Cline, VS Code, GitHub Copilot, Codex, n8n, LibreChat and OpenWebUI. The Free plan costs nothing and allows 200 requests per day. Pay as you go costs $5 a month, with a 5% markup on model cost. Enterprise pricing is custom. Requesty is available via API and web; self-hosting is not offered.

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.