LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
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☁️ Build multimodal AI applications with cloud-native stack
- neural-search
- cloud-native
- deep-learning
- machine-learning
Jev-like family of decision models built on top of Qwen3.5/3.8 you can train and run on your own
- decision-model
- jev
- qwen3
Open-source inference platform for language, vision, embedding, reranking, image, audio, and video models. Deploy with multiple engines across heterogeneous hardware, from a laptop to a distributed cluster. Serve models through OpenAI-compatible APIs.
A framework for efficient model inference with omni-modality models
- diffusion
- inference
- model-serving
- pytorch
ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
- version-control
- experiment-manager
- version
- control
Statistical Machine Intelligence & Learning Engine
- machine-learning
- regression
- clustering
- manifold-learning
Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes
- knative
- machine-learning
- model-interpretability
- model-serving
A GPU cluster manager for high-performance AI model serving (vLLM, SGLang) and on-demand SSH-accessible GPU instances.
Dockerized OpenAI-compatible wrapper for Kokoro-82M text-to-speech w/multiplatform CPU, AMD, NVIDIA GPU PyTorch; multi-speaker, clone-tuning, caption timestamps, SSML, websockets, optional readalong web UI
Translatedcube studio is an open-source, cloud-native, one-stop machine learning / deep learning / large model AI platform. It covers the full mlops algorithm pipeline, a computing power rental platform, online notebook development, drag-and-drop task flow pipeline orchestration, multi-machine multi-GPU distributed training, hyperparameter search, inference services with VGPU virtualization, edge computing, a labeling platform with automated labeling, SFT fine-tuning / reward model / reinforcement learning training for large models such as deepseek, multi-machine large model inference with vllm/ollama/mindie, a private knowledge base, and an AI model marketplace. It supports domestic Chinese CPUs/GPUs/NPUs and the Ascend ecosystem, supports RDMA, and supports distributed frameworks such as pytorch/tf/mxnet/deepspeed/paddle/colossalai/horovod/ray/volcano.
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
- kubernetes
- machine-learning
- deployment
- serving
A minimal Python framework for building custom AI inference servers with full control over logic, batching, and scaling.
- ai
- api
- serving
- artificial-intelligence
🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.
- fastapi
- streamlit
- pydantic
- python
cubestudio开源云原生一站式机器学习/深度学习/大模型AI平台/MaaS/mlops/人工智能平台/训推平台，算法全链路流程，多租户，算力租赁平台，token中转，拖拉拽任务流pipeline编排，多机多卡分布式训练，超参搜索，推理服务，VGPU虚拟化，云边端协同，边缘计算，自动化标注平台，deepseek等大模型sft微调/奖励模型/强化学习训练，vllm/ollama/mindie大模型多机推理，私有知识库llmops智能体，AI模型市场，支持国产异构算力调度,昇腾/寒武纪/海光/摩尔/沐曦等，支持ib/roce/RDMA，信创支持
A unified orchestration layer for heterogeneous AI compute. It standardizes how to manage compute and run training and inference on GPU clouds, Kubernetes, VMs, or bare-metal clusters.
- machine-learning
- python
- gpu
- llms
High Performance Serving Runtime For Interactive Super Intelligence System
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