model_server
A scalable inference server for models optimized with OpenVINO™
OpenVINO Model Server (OVMS) is a high-performance inference server that exposes AI models through standard network APIs, including OpenAI-compatible endpoints and KServe protocols. Built on Intel's OpenVINO toolkit, it serves both generative AI workloads (LLMs, vision-language models, text embeddings, image generation, audio) and classic deep learning models with optimized performance on Intel CPUs, GPUs, and NPUs. Developers can deploy models from HuggingFace or local storage via Docker, bare metal, or Kubernetes, with support for model versioning, hot-reload, and multi-format models (TensorFlow, ONNX, OpenVINO IR, GGUF).
Key Features
Use Cases
- 01Serving quantized LLMs like Qwen, Llama, or Mistral with OpenAI-compatible chat completion APIs
- 02Building AI agents that leverage vision-language models for multimodal understanding
- 03Deploying text embedding models for semantic search and retrieval-augmented generation (RAG)
- 04Running image classification, object detection, or OCR models with KServe protocols
- 05Generating images from text prompts using Stable Diffusion or similar models
- 06Providing speech-to-text and text-to-speech services through OpenAI audio endpoints
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model_server — FAQ
What is OpenVINO Model Server?+
OpenVINO Model Server (OVMS) is a C++ inference server that exposes machine learning models through OpenAI-compatible and KServe APIs, optimized for Intel hardware. It supports both generative AI workloads (LLMs, VLMs, embeddings) and classic deep learning models.
How do I install and run OpenVINO Model Server?+
Pull the Docker image with 'docker pull openvino/model_server:latest' and run it with your model path, or download the binary package from GitHub Releases for bare-metal Linux/Windows deployment. Models can be automatically downloaded from HuggingFace or loaded from local storage, S3, GCS, or Azure Blob.
Which AI clients work with OpenVINO Model Server?+
Any client supporting OpenAI's API format (for LLMs and embeddings) or KServe/TensorFlow Serving protocols (for classic models) can connect. This includes Python's OpenAI library, Triton client libraries, and custom applications using gRPC or REST.
Do I need API keys or special hardware to use OVMS?+
No API keys are required; the server runs entirely on your infrastructure. While optimized for Intel CPUs, GPUs, and NPUs, OVMS runs on standard x86 hardware. GPU acceleration requires Intel integrated or discrete graphics.
Is OpenVINO Model Server free to use?+
Yes, OVMS is open-source software licensed under Apache 2.0, available at no cost for both commercial and non-commercial use.
How does OVMS integrate with AI agents and MCP?+
OVMS provides inference backends for AI agents through its OpenAI-compatible API, enabling agents to call LLMs, embeddings, and vision models. The documentation mentions support for AI agents with MCP servers for agentic workloads.
How do I install model_server?+
Open the source repository on GitHub and follow its README. model_server is a mcp server — MCP Agents Market links you directly to the official repo.
Is model_server free?+
model_server is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.