GPUStack

GPU cluster manager that orchestrates inference engines like vLLM and SGLang. Automated engine selection, parameter optimization, and distributed multi-GPU deployment for high-performance AI workloads.

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vLLM

vllm-project/vllm

State-of-the-art serving engine with PagedAttention and continuous batching. Currently the fastest production-grade LLM server.

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llm-d

llm-d/llm-d

Kubernetes-native distributed LLM inference framework. Donated to CNCF by RedHat, Google, and IBM. Intelligent scheduling, KV-cache optimization, and state-of-the-art performance across accelerators.

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LMDeploy

InternLM/lmdeploy

Toolkit for compressing, deploying, and serving LLMs from OpenMMLab. 4-bit inference with 2.4x higher performance than FP16, distributed multi-model serving across machines.

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TokenSpeed

lightseekorg/tokenspeed

LLM inference engine for agentic workloads with a C++ scheduling control plane, Python execution plane, modular kernels, and KV-cache lifecycle management. MIT licensed.

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vLLM-Omni

vllm-project/vllm-omni

Multi-modal inference stack extending vLLM for image, audio, and video generation workloads with a unified serving interface. Apache 2.0 licensed.

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LMCache

LMCache/LMCache

Supercharge LLM inference with the fastest KV Cache layer. 3-10x delay savings and GPU cycle reduction for multi-round QA and RAG. Integrates seamlessly with vLLM for distributed, high-throughput deployments. Apache 2.0 licensed.

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