# Ollama Local LLM Runner for Windows PC - **Name:** Ollama Local LLM Runner for Windows PC - **Version:** 0.40.9 - **Developer:** Ollama Inc. - **License:** Open Source - **Platform:** Windows - **Requires:** Windows 10 / 11 - **File type:** EXE Installer - **Size:** 1.55 GB - **Category:** Graphics & Design - **Updated:** 2026-10-23 - **SHA-256:** 67f57180b35691eb5e017388c3125ea96e41b3b6a55b84387bb71fd65c5530f9 - **Canonical page:** https://filecobra.com/app/ollama-local-llm-runner-pc/ - **Download page:** https://filecobra.com/download/ollama-local-llm-runner-pc/ - **Direct download:** https://ollama.com/download/OllamaSetup.exe > Ollama runs large language models entirely on your own PC — Llama, Qwen, Mistral, DeepSeek and more — with one command, a local API, and zero data leaving your machine… Ollama is a free, open-source tool that makes running large language models locally as simple as running a container image: install it, run 'ollama run llama3.2', and you are chatting with an AI model that lives entirely on your machine. It manages model downloads (hundreds of models — Llama, Qwen, Mistral, Gemma, DeepSeek, Phi, vision and embedding models), serves them through a local REST API compatible with developer tooling, accelerates on NVIDIA and AMD GPUs automatically, and exposes integrations for coding assistants, chat UIs, and frameworks like LangChain. Nothing you type leaves your PC, there are no API fees, and it works fully offline once a model is downloaded. This download is the official Windows installer from ollama.com. ## Installation 1. **Download and run OllamaSetup.exe** — Download Ollama from the official ollama.com link on this page and run the installer. It sets up a background service and the ollama command. 2. **Pull your first model** — Open a terminal and run: ollama run llama3.2 — Ollama downloads the model (a few GB) and opens a chat prompt immediately. 3. **Use it from apps and code** — Ollama serves an API on localhost:11434. Point chat UIs (Open WebUI, etc.), editor assistants, or your own code at it — no internet or keys required. ## Editorial verdict Ollama did for local AI what Docker did for servers: it turned a weekend of CUDA errors and Python environments into one command. On a typical Windows machine with a mid-range NVIDIA GPU, you install the app, type 'ollama run qwen3' or 'ollama run llama3.2', and within minutes you are chatting with a capable model that runs entirely locally — no account, no API bill, no prompt ever leaving your desk, and full function on a train with no Wi-Fi. The library covers the open-weights world (Llama, Qwen, Mistral, Gemma, DeepSeek distillations, vision models, embeddings), quantization is handled sensibly so models fit in consumer VRAM, and the local REST API has become a de-facto standard that chat UIs, coding tools, and frameworks target directly. The honesty box: local models are bounded by your hardware. A laptop with 8 GB RAM will run small models (3–8B) at usable speeds and will not run a 70B well no matter what the marketing implies; generation quality trails the giant hosted frontier models, and large downloads (10–40 GB per big model) tax storage. Ollama also focuses on inference, not training or fine-tuning. But as the standard front door to private, free, offline AI — for developers prototyping without API costs and for anyone who simply refuses to send their documents to a cloud — it has no serious rival. Install it once and every other AI tool on your machine gets better. ### Strengths - One command from install to chatting: ollama run handles download, quantization selection, GPU acceleration and serving automatically. - Complete privacy and zero marginal cost — prompts never leave your machine, no API keys or subscriptions, works fully offline. - Huge model library with sensible defaults: Llama, Qwen, Mistral, Gemma, DeepSeek, vision and embedding models, managed like container images. - A clean local REST API (plus OpenAI-compatible endpoints) that chat UIs, editor assistants and LangChain-style frameworks already speak. - Free and open source (MIT) from Ollama Inc. — this is the official Windows installer from ollama.com. ### Trade-offs - Your hardware is the ceiling: large models need serious RAM/VRAM, and small laptops will only run small models at polite speeds. - Open-weights local models trail the biggest hosted frontier models on hard reasoning — the privacy/cost trade is real, if usually worth it. - Model files eat disk fast (popular models run 5–40 GB each), and Ollama is inference-only — no training or fine-tuning workflows. ## FAQ **Is Ollama free?** Yes — free and open source under the MIT license. Models are downloaded from the Ollama library at no cost (each under its own license), and there are no API fees because everything runs on your PC. **What PC do I need to run models?** Any Windows 10/11 PC can run small models (1–8B parameters) on CPU with 8–16 GB RAM, slowly to comfortably. A discrete NVIDIA or AMD GPU with 8 GB+ VRAM makes mid-size models genuinely fast. Bigger models need proportionally more memory. **Does Ollama work offline?** Yes. After a model is downloaded, chats and the API work with no internet connection at all — one of its main advantages over cloud AI. **Which models can I run?** Hundreds from the Ollama library: Llama 3.x, Qwen 3, Mistral, Gemma 3, DeepSeek distillations, Phi-4, vision models like LLaVA, and embedding models — in sizes from 1B to 70B+. **Is this the official Ollama download?** Yes — this page links OllamaSetup.exe from ollama.com's own download host. OllamaSetup.exe is an evergreen installer; the version and SHA-256 recorded on this page are those of the build we verified. --- Source: https://filecobra.com/app/ollama-local-llm-runner-pc/ · Mirrored from the publisher's own release channel by FileCobra. FileCobra runs no antivirus lab of its own.