model-serving

A high-throughput and memory-efficient inference and serving engine for LLMs

The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!

A framework for efficient model inference with omni-modality models

LightLLM is a Python-based LLM (Large Language Model) inference and serving framework, notable for its lightweight design, easy scalability, and high-speed performance.

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.

Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs

High-performance inference framework for large language models, focusing on efficiency, flexibility, and availability.

Community maintained hardware plugin for vLLM on Huawei Ascend

MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.

RTP-LLM: Alibaba's high-performance LLM inference engine for diverse applications.

SGLang-Omni is a high-performance serving framework for audio models (TTS, ASR) and unified multimodal models.

The simplest way to serve AI/ML models in production

A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine

Serverless LLM Serving for Everyone.

Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One command to load, one command to serve. 336x faster than Python inference.

FastAPI Skeleton App to serve machine learning models production-ready.

Python + Inference - Model Deployment library in Python. Simplest model inference server ever.

JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs (and GPUs in future -- PRs welcome).

The missing bridge between your ML models and your AI agents.

Learn to serve Stable Diffusion models on cloud infrastructure at scale. This Lightning App shows load-balancing, orchestrating, pre-provisioning, dynamic batching, GPU-inference, micro-services working together via the Lightning Apps framework.