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To use Ollama models in Visual Studio Code, install the official Ollama extension, start Ollama, then choose a model in VS Code Chat. The extension requires Visual Studio Code 1.127 or newer, a running Ollama server, and at least one model available through Ollama. Local models do not require sign-in; cloud models may prompt you to sign in.
What you need before setting it up
- Visual Studio Code version 1.127 or newer.
- Ollama installed and running on your computer.
- At least one local or cloud model available in Ollama.
Ollama 0.17.6 or newer is recommended for cloud-model sign-in and richer model metadata. Older Ollama versions may still work with local models. See Ollama’s VS Code extension documentation.
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Install the official Ollama extension and select a model
- Install the official Ollama extension from the Visual Studio Code Marketplace.
- Start Ollama. By default, the extension discovers models from
http://127.0.0.1:11434. - If Ollama has no model available yet, add one. Ollama’s documentation gives
ollama pull qwen3.6as a local-model example. For a cloud-model example, it showsollama pull kimi-k2.6:cloud, followed byollama signin. These are examples, not recommendations for every task or computer. - Open Chat in VS Code and open the model picker at the bottom of the chat input.
- Choose a model listed under the Ollama section, then send a prompt in Chat.
The local and cloud examples, along with the default discovery endpoint, are documented in Ollama’s VS Code integration guide.
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Choose between a local and cloud model
A local model runs through the Ollama installation on your computer; a cloud model uses Ollama’s cloud offering. Ollama states that local models do not require sign-in. A cloud model may require authentication, in which case run ollama signin when prompted. The cited setup documentation does not establish a general privacy, cost, or performance comparison between the two options.
#1 Best Overall
VZMORE AX9 Max Mini PC, V-Cooling（ Vapor Chamber）, Ryzen AI 9 HX 470
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- ENGINEERED FOR LONG-TERM RELIABILITY + 3-YEAR PRODUCT SUPPORT — The VZMORE AX9 Max mini desktop computer combines a durable chassis with an optimized air-intake design for efficient cooling and long-term stability. VZMORE micro pc undergo extensive testing for sustained workloads, thermal balance, acoustics, power stability, port durability, multi-display compatibility, network reliability, memory and storage integrity, and system stability. Backed by a 3-year product support and 24/7 customer support, AX9 Max delivers dependable performance for everyday use.
Use the current provider setup
Older setup guides may refer to VS Code’s built-in Ollama provider. Microsoft’s current language-model documentation marks that provider as deprecated and directs users to install the official Ollama extension for local models. Use the extension workflow above rather than relying on instructions for the deprecated provider: Microsoft’s VS Code language-model documentation.
Fix models missing from the picker
- Confirm Ollama is running and check that a model is available with
ollama list. - In VS Code, open the Command Palette and run
Ollama: Refresh Models. - If the model still does not appear, run
Ollama: Diagnose Modelsand inspect the Ollama output channel for diagnostic details. - If a cloud model asks for authentication, run
ollama signin.
These checks follow the troubleshooting steps in the Ollama extension documentation and Ollama’s VS Code integration guide.
Rank #2
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- Intelligent AI Assistant: Mini PC AI X1 Pro has a built-in new Copilot AI function and supports Recall function - just describe the details in your memory to retrieve the content you have recently browsed or used. At the same time, the built-in real-time subtitle translation provides subtitles simultaneously during video calls or watching movies. Press the dedicated Copilot button to activate the AI assistant in Windows 11, quickly answer questions, inspire creativity and improve work efficiency. In addition, the fingerprint sensor realizes fast and secure unlocking.
- Extreme audio experience and efficient noise reduction: Equipped with dual noise reduction DMIC and built-in speakers, you can enjoy clear and noise-free sound quality experience in video conferencing, audio and video entertainment and voice interaction. The audio system and AI assistant work seamlessly together to ensure intelligent and efficient workflows.
- High-speed connection and strong expansion performance: Equipped with dual USB4 interfaces to ensure fast and unimpeded data transmission and support connecting to eGPU through the OCuLink port, opening up a super-smooth gaming experience and a stunning visual feast. Supports three ultra-fast PCIe 4.0 SSDs(Total 2TB), supports a loading speed of up to 7000MB/s, and can be expanded to up to 12TB of storage; it is also equipped with up to 96GB 5600MHz DDR5 removable memory (up to 128GB), allowing multitasking with ease.
- Intelligent Cooling Design & Energy Saving: The CPU and SSD are equipped with independent fans, and the memory and built-in power supply adopt efficient heat dissipation design, which further enhances the heat dissipation performance. Even under high load, it can keep the full load noise as low as 45dB and the maximum power consumption of 65W; built-in 135W power adapter to reduce stability issues and noise related to the power adapter connection.
Address context-length needs for local models
VS Code may show a model’s maximum supported context length even when Ollama allocates a smaller context at runtime. For the documented local-model flow, Ollama instructs users to open Ollama Settings, set the context length to at least 64k, reload the VS Code window, and resend the prompt. This setting is a documented way to address context needs, not a guarantee that every model or device will perform well at that size. See Ollama’s integration instructions.
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Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the setup documentation does not establish
The reviewed official integration sources do not specify suitable CPU, GPU, memory, or storage requirements, or publish comparative local-inference benchmarks. They therefore do not support a universal hardware recommendation or a claim that a particular model will run well on every computer.
Quick Recap
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MINISFORUM AI X1 Pro-470 Mini PC, AMD Ryzen AI 9 HX470 (12C/24T, up to 5.2 GHz), Radeon 890M, 4K Quad-Display, Dual 2,5G LAN, Wi-Fi 7, Bluetooth 5.4, OCuLink(NO RAM/SSD/OS)
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