How to Run AI Locally on Windows 11 Using PowerToys and Ollama for Privacy and Speed

Artificial intelligence has become a permanent fixture in the landscape of modern computing, seamlessly woven into daily routines through digital assistants, productivity suggestions, and—perhaps most pervasively—AI chatbots. For users entrenched in the Windows ecosystem, the evolving integration of AI is driving new workflows, innovation, and, sometimes, growing skepticism about privacy and cloud dependency. But while services like Copilot and ChatGPT dominate headlines, they are frequently tethered to the cloud, raising concerns over data sovereignty, reliability, and ongoing cost. For those wishing to tap the power of large language models without sending queries to remote servers, a new breed of local AI solutions is emerging—offering both flexibility and enhanced privacy.

Why Run AI Locally? Critical Reasons and Real-World Scenarios​

Before delving into the mechanics of building a local AI chatbot with PowerToys and Ollama, it’s worth examining why local operation matters in the age of all-encompassing cloud AI. The default for many consumer-grade chatbots is to process data remotely, which presents several drawbacks:

• Privacy and Data Sovereignty: All input and conversational data is routed through external servers, creating a trail susceptible to interception or unintended retention. Local deployment allows users to keep sensitive business queries, personal information, and creative ideas strictly on their own machines.
• Reliability and Latency: Cloud-based AI depends on solid internet connections and the reliability of third-party servers. Local AI runs at the speed of the hardware, immune to downtime from API endpoints or throttling from service providers.
• Cost and Customization: Usage restrictions, subscription costs, and API quotas can make heavy or enterprise-wide use of cloud AI expensive. Running AI locally means operating within the limits of your own resources, free from imposed financial barriers or model choices.

For developers, knowledge workers, and privacy enthusiasts, the ability to harness the capabilities of large language models (LLMs) on a Windows device marks a compelling new frontier.

Demystifying the Stack: PowerToys Run Meets Ollama​

The innovation at hand fuses Microsoft's popular PowerToys suite for Windows 11 with Ollama, a cutting-edge open-source project that simplifies running LLMs directly on consumer hardware. The process is straightforward but technical—the intersection of user-friendly Windows extensions and the raw power of command-line AI deployment.

PowerToys Run: Windows Power User’s Swiss Army Knife​

PowerToys is Microsoft’s open-source toolkit aimed at expanding Windows with features power users crave, such as window management, advanced shortcuts, and the highly configurable “PowerToys Run.” Acting as a fast launcher and utility finder (akin to macOS Spotlight), PowerToys Run is both scriptable and extensible through plugins. These plugins enable users to trigger custom workflows quickly—now including, thanks to the community, a locally-executed AI chatbot.

Ollama: Local LLMs Without PhD-Level Hassle​

Ollama is designed to bring generative AI models to everyday machines. It packages well-known large language models—like Meta’s Llama, Mistral, and more—into container-like environments that operate entirely on your hardware. While seasoned developers are already familiar with frameworks like PyTorch and TensorFlow, Ollama streamlines the process, providing a command-line interface that vastly simplifies deployment, model switching, and updates. Crucially, Ollama supports GPU acceleration via AMD and NVIDIA cards, which is necessary for timely responses with today’s state-of-the-art LLMs.

Step-by-Step: Turning PowerToys into an AI Chatbot​

Setting up a functioning, privacy-focused chatbot on Windows 11 using these tools is remarkably accessible—especially considering the sophistication behind the scenes.

Prerequisites and Hardware Considerations​

• Windows 11 PC: PowerToys and Ollama both operate best on Windows 11, though earlier compatibility may exist for PowerToys.
• Discrete GPU (AMD or NVIDIA): While Ollama can run CPU-bound, performance scales dramatically with a modern mobile or desktop graphics card. The experience with slower CPUs or integrated graphics may be less ideal, with laggy or truncated responses.
• PowerToys Installed: Available via the Microsoft Store, GitHub, or winget, install PowerToys if not already present.
• Ollama Installed: Download from the official repository on GitHub, following the platform-specific installation instructions.

Installing Ollama and Downloading Llama 3.1​

Ollama provides a simple mechanism for pulling and running models. Once the software is installed, open PowerShell (or your preferred terminal) and type:
ollama pull llama3.1
Llama 3.1 is the default model choice for the plugin—selected for compatibility rather than recency, but substitutable with other supported models if desired. This modularity is crucial for users with particular requirements, be it for accuracy, speed, or conversational nuance.

Integrating PowerToys-Run-LocalLLM: The Plugin Bridge​

With the core AI engine ready, the bridge to PowerToys Run comes from a community-developed plugin: PowerToys-Run-LocalLLM. This plugin acts as the intermediary, listening for queries from PowerToys Run and piping them to Ollama, then presenting responses inline—no external calls or browser detours.
Installation involves:

• Downloading the plugin from its official GitHub page.
• Extracting the plugin to the appropriate directory, typically:
  %LOCALAPPDATA%\Microsoft\PowerToys\PowerToys Run\Plugins
• Restarting PowerToys to register the new capability.

From here, a simple keyboard shortcut brings up PowerToys Run. Users type llm followed by their query—e.g., llm Draft an email to my boss about the project status—and, after a short wait, receive a response generated entirely on their PC.

Potential Hurdles and Their Solutions​

The integration isn’t without quirks. Two main limitations stand out:

• Output Truncation: PowerToys Run’s results pane is limited by default, leading to clipped responses for longer outputs generated by the AI. The workaround: Increase the “Number of results shown before scrolling” setting in PowerToys, which enlarges the response area. This improves the amount of visible text but doesn’t add scrolling—a future improvement that plugin developers may address.
• Perceived Slowness: Unlike the dynamic, word-by-word streaming familiar to web-based AI chatbots, the plugin delivers the entire response at once. This blank interval can feel sluggish, especially with complex prompts or on modest hardware. However, under the hood, Ollama processes the request with similar efficiency as in the terminal; the bottleneck is presentation rather than computation.
• Hardware Dependency: High performance relies on sufficient GPU power. Users with cutting-edge cards like the NVIDIA RTX 5080 report near-instantaneous results. Older machines may experience significant wait times or truncated outputs—an area where future model optimizations or plugin refinements could help.

Security and Privacy: A Measured Assessment​

The top value proposition for this configuration is local processing, but what does that mean in a practical, security-conscious sense? Critics of cloud-based AI frequently cite data sovereignty—where your queries, ideas, or proprietary information are stored and who has potential access. With a local solution:

• No Third-Party Data Transmission: All message handling and inference are strictly confined to your machine. This removes exposure to cloud breaches, subpoena risk, and alignment with privacy regulations like GDPR.
• Model Weights and Data Custody: You control which models are installed, where they reside, and whether updates are applied. This ownership ensures you are not caught off guard by vendor-driven changes or service deprecations.
• Caveats: Local does not mean invulnerable. Any process running on your PC could be monitored or exploited by malware, and untrusted plugins or models imported from unofficial sources could pose risks. As always, a strong baseline of endpoint security, cautious download behaviors, and regular updates are essential.

From an enterprise perspective, this approach is particularly enticing for regulated industries—healthcare, finance, government—where cloud data residency is a dealbreaker but the utility of AI remains high.

Flexibility, Customization, and the Future of Desktop AI​

One of the strongest arguments in favor of the PowerToys-Ollama approach is its extensibility. Unlike single-purpose chatbots or closed platforms:

• Model Choice: Users are not locked into a specific brand or behavior. Ollama supports various LLMs, from Llama to Mistral and beyond, allowing experiments with nuance, speed, and domain-specific tuning.
• Update Agility: You can trial new models or revert to known-stable versions instantly, avoiding vendor-imposed upgrades or licensing changes.
• Automation and Scripting: Since Ollama is a command-line tool, users can automate queries, chain outputs to scripts, or even integrate results into local databases—all without an active internet connection.

For researchers and developers, the ability to use local models with PowerToys plugins democratizes AI experimentation—no cloud credits required, and no fear of API shutdowns interrupting ongoing work.

Real-World Use Cases: Practical Productivity on Windows 11​

The PowerToys Run integration brings AI to the forefront of the keyboard workflow. Rather than disrupting concentration with browser tabs or external apps, users trigger natural language capabilities inline with the tools they already use.
Some tangible scenario examples include:

• Instant Summaries: Paste a block of business text and let the local LLM craft a concise executive summary, right from the launcher.
• Technical Explanations: Get Python snippets explained or Windows registry tweaks outlined—without ever leaving the desktop or risking proprietary code on an external server.
• Creative Drafting: Rapidly generate email drafts, brainstorm outlines, or rephrase feedback in different tones—all captured locally.
• Contextual Memory: Because the interface is your own machine, it’s possible, with some scripting, to maintain user-specific context or tie AI responses to local files, unlike the stateless environment of most cloud chatbots.

Critical Analysis: Strengths, Weaknesses, and What Lies Ahead​

Strengths​

• Privacy by Default: Conversation history and inputs never leave your machine unless you choose to share them.
• Speed (Hardware Dependent): On capable systems, response times rival or outperform web-based alternatives.
• Custom Model Flexibility: Try bleeding-edge or domain-specific LLMs as soon as they are released, without waiting for cloud deployment or license agreements.
• Workflow Integration: Embedding AI inline with familiar PowerToys Run workflows reduces cognitive load and context switching, boosting productivity.

Weaknesses and Potential Risks​

• Setup Complexity: While approachable for power users, the average consumer may find the onboarding—CLI tools, plugin directories, GPU requirements—intimidating compared to a web signup.
• Performance Variability: Hardware constraints dramatically affect usability. On low-end GPUs or CPUs, response times may discourage regular use.
• User Interface Limitations: The current output area, lacking scrolling or formatting, hampers long-form work or research-type responses.
• Maintenance Overhead: As with all DIY solutions, model updates, security patches, and PowerToys/plugin compatibility must be managed by the user. Semantic drift between Ollama releases and plugin expectations could break functionality.
• Trust in Plugins: Community-developed plugins drive innovation but also risk introducing vulnerabilities if not properly vetted. Users must exercise discretion, ideally preferring open source and well-discussed projects.

Unverified Claims and Forward-Looking Cautions​

Some user anecdotes suggest the local setup rivals the interactivity and speed of cloud Copilot on the latest graphics cards. While benchmarks from independent reviewers broadly support this in inference mode, consistency depends on prompt complexity, system load, and continuous plugin improvement. Interested readers should verify compatibility, especially with evolving Windows or PowerToys updates, before betting on this as a daily driver.

Broader Implications: The Local AI Renaissance for Windows​

Microsoft’s own push to embed AI—via Copilot and similar features—signals the direction of travel for consumer and enterprise Windows experiences. But there is palpable demand among enthusiasts and knowledge workers for solutions that run on their terms, on hardware they manage and trust. PowerToys remains one of the most popular productivity upgrades for Windows 11, beloved for its flexibility and rapid feature addition. Tying local LLMs to this ecosystem hints at a rich future for open-source, privacy-conscious AI on the desktop.
The coming years may see more official plug-and-play integrations, friendlier UIs, and hardware optimizations that bring local AI to the masses. In the meantime, for those willing to dig a little deeper, PowerToys plus Ollama—connected via a simple plugin—offers a tantalizing look at the next stage of AI democratization: fast, local, private, and astoundingly useful.

Conclusion: Who Should Try This, and Why?​

For privacy advocates, technical tinkerers, developers, and anyone looking to reclaim ownership of their digital conversations, the PowerToys and Ollama AI stack delivers both practical utility and philosophical alignment. The setup process rewards a willingness to experiment, and the gains—for privacy, flexibility, and workflow efficiency—are substantial.
Windows 11 power users now have the option to summon AI’s capabilities at a keystroke, bounded entirely by their local resources and control. As the line between cloud convenience and local sovereignty continues to shift, solutions like this will become ever more valuable—not just as technical novelties, but as essential building blocks for a secure, productive, and personalized digital future.
If you’ve ever wished to embed a hyper-capable AI directly into your workflow, with zero data leaving your machine, this community-powered solution is proof positive that the future of Windows AI isn’t just in the cloud—but right under your fingertips.

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Source: inkl I turned PowerToys into an AI chatbot, and you can too — All your AI chats on your local machine