Run 100+ open-source LLMs locally with a simple REST API, the easiest way to self-host language models on your VPS.
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Run 100+ open-source LLMs locally with a simple REST API, the easiest way to self-host language models on your VPS.
Ollama is an open-source platform designed to simplify running large language models (LLMs) on your own infrastructure. Launched on GitHub, it has quickly become the standard for self-hosting models like Llama, Phi, Mistral, Gemma, and DeepSeek, with over 100,000 developers using it for private AI deployments.
Completely free under the MIT License, no API fees, usage limits, or hidden charges. Everything model weights, inference requests, and response logs, lives on your own server. From developers prototyping local AI assistants to enterprises building compliant internal chatbots, Ollama puts full control back in your hands.
A VPS keeps Ollama running 24/7, ensuring your language models are always ready to respond, even when your local machine is offline. Critical for production chatbots, automated content generation, or real-time data enrichment tasks that need low-latency responses at any hour.
Start with a basic VPS plan and upgrade CPU, RAM, or add GPU acceleration as your inference demand grows. Ollama can handle hundreds of concurrent requests with proper resource allocation, making it ideal for teams moving from prototyping to production without re-architecting.
AccuWeb’s Linux VPS environment is fully compatible with Docker, letting you deploy Ollama with the official image in minutes. Full root access lets you mount model storage volumes, configure GPU passthrough, and expose the REST API securely behind your own domain with HTTPS.
Ollama provides one-command download and execution for over 100 open-source models, including Llama, Phi, Mistral, Gemma, and DeepSeek, with automatic quantisation and hardware optimisation.
The OpenAI-compatible chat endpoint lets you swap out proprietary APIs instantly, while the powerful CLI enables scripting, model management, and direct inference from the terminal.
Create custom models by modifying system prompts, temperature, context length, and other parameters, or import any GGUF file from Hugging Face for maximum flexibility.
Ollama automatically detects and uses NVIDIA CUDA, AMD ROCm, or Apple Metal GPUs, and can split large models across multiple GPUs for significantly faster token generation.
The same Ollama binary runs on Linux, Windows, and macOS, with resource-friendly quantized models that can run on as little as 2GB of RAM or low-end VPS instances.
Deploy a fully internal AI assistant for HR, IT, or customer support without sending any conversation data to external APIs. Perfect for companies handling sensitive information or requiring complete audit trails.
Integrate Ollama into IDEs and CI/CD pipelines to automate code completion, generate unit tests, review pull requests, and document legacy codebases using models like CodeLlama or DeepSeek-Coder.
Process internal reports, contracts, research papers, or meeting transcripts locally. Extract key insights, generate summaries, and answer natural language questions without exposing documents to cloud providers.
Generate marketing copy, blog posts, social media captions, and creative writing with no usage caps or per-token fees. Experiment with different models and prompts to refine your unique brand voice.
Run cutting-edge open models without rate limits or usage caps. Test prompting strategies, fine-tune on custom datasets, and benchmark performance across architectures - all on infrastructure you control.
Pair Ollama with automation tools to trigger AI inference from webhooks, databases, or schedules. Automate email drafting, ticket classification, data extraction, and customer response generation entirely on your own VPS.
AccuWeb's Linux VPS infrastructure is purpose-built for GPU-accelerated AI workloads like Ollama. With high-speed storage for fast model loading and 24/7 hardware monitoring, your large language model inference runs on infrastructure specifically optimised for low-latency token generation.
When you self-host Ollama on AccuWeb, every prompt, model weight, and generated response stays within your own server environment; no third-party API provider can log your conversations, mine your data, or change pricing terms overnight. Our global data center network across the US, UK, Germany, India, and Singapore lets you deploy your Ollama instance closest to your users, minimizing response latency for real-time chat applications.
Our SOC 2 Type II and ISO/IEC 27001 certifications mean your infrastructure meets enterprise compliance standards, while our optional GPU-accelerated VPS plans deliver the raw compute power Ollama needs to run 70B-parameter models at production speeds. With full root access and Docker pre-installed, you can be serving Llama 3 through a REST API in under ten minutes.
Ollama is a lightweight, open-source tool that packages and runs large language models on your own hardware. It handles model downloads, quantization, GPU acceleration, and exposes a simple REST API or CLI, removing all the complexity of deploying LLMs. Think of it as "Docker for LLMs" - but even simpler.
Pull the official ollama/ollama image, run the container with GPU flags if available, and mount a volume for persistent model storage. Then expose port 11434 and access the API from anywhere. AccuWeb's Linux VPS plans with GPU support make this ready in under five minutes.
Yes. Ollama provides an OpenAI-compatible endpoint (/v1/chat/completions), so any existing client (LangChain, Continue, Open WebUI) can switch to your self-hosted Ollama instance by simply changing the base URL. No code changes required.
Ollama runs on almost any VPS. For small models (7B parameters or less), a CPU-only VPS with 4-8GB RAM works fine. For larger models (13B-70B), GPU-accelerated VPS plans deliver significantly faster responses. Quantized versions reduce memory usage dramatically.
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