vLLM Alternatives

Direct alternatives to vLLM

vLLM is an Apache-2.0 serving engine built around PagedAttention, aimed at high-throughput serving on datacenter accelerators. People look at alternatives when a workload leans on shared prompt prefixes or structured output, when they want one serving stack across more hardware vendors, or when the target is a laptop, a CPU or an edge device rather than a GPU server. The list below is grouped by where the model will run.

Serving on GPU servers

• SGLang: an Apache-2.0 serving framework whose RadixAttention reuses KV cache across requests with overlapping prefixes, which helps multi-turn chat and few-shot prompting. It adds constrained JSON output and a frontend language for multi-call programs. SGLang is also used as the rollout backend in several RL post-training stacks.
• Modular: MAX is a serving framework with an OpenAI-compatible API that targets NVIDIA, AMD, Google TPU, AWS Trainium and Apple GPUs among others. Modular's site describes self-hosting as free (September 2026), though the stack is not Apache-licensed like vLLM.

Laptops, CPUs and edge hardware

• llama.cpp: a C/C++ engine with GGUF quantization across CPUs, GPUs and Apple Silicon. Fits single-user and on-device work, where vLLM is a poor match (it does not list Windows support and serves Apple Silicon through a separate vLLM-Metal project).
• Project Zero: an MIT-licensed C99 engine for BitNet ternary and GGUF models on CPU only, built as one binary with an OpenAI-compatible server. Early-stage, with a single tagged release (v0.1.0, June 2026) and one primary maintainer.
• Roofline: a commercial compiler and device runtime built on MLIR and IREE for the CPUs, GPUs and NPUs inside industrial, automotive, robotics and mobile hardware. Pricing is quoted through sales.