SGLang
Serving runtime for large language and vision models built around RadixAttention prefix caching, a zero-overhead batch scheduler and structured-output decoding, behind an OpenAI-compatible API.
Compare 3 reviewed substitutes for TensorRT-LLM
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Serving runtime for large language and vision models built around RadixAttention prefix caching, a zero-overhead batch scheduler and structured-output decoding, behind an OpenAI-compatible API.
High-throughput inference and serving engine for LLMs — PagedAttention, continuous batching, and tensor/pipeline parallelism keep GPUs saturated across concurrent callers, behind an OpenAI-compatible API.
Managed inference platform for open and custom models — dedicated GPU deployments, autoscaling to zero, and a model-packaging format that moves the same artifact between your cloud and theirs.
The top alternatives to TensorRT-LLM include SGLang, vLLM, Baseten. These ai platforms tools offer similar functionality with different pricing, features, and architectural approaches.
Yes, TensorRT-LLM is open source. You can use it without paying.
Consider your team size, budget, technical requirements, and existing stack. Compare features like scalability, integrations, pricing model, and community support. Our side-by-side comparison pages can help you evaluate specific pairs.
TensorRT-LLM is a ai platforms tool. It competes with SGLang, vLLM, Baseten in the ai platforms space.