You can set up a local AI assistant by installing a model runner, downloading a model, loading it into your computer’s memory, and chatting with it. For a beginner, LM Studio offers a guided desktop workflow; Ollama is a good alternative if you prefer a command line. Your computer’s memory and processing hardware determine which models are practical and how quickly they respond. A local model can process prompts on your device, but downloads require internet, and any separately configured cloud provider or tool may still receive your data.
What “local AI assistant” means
A model runner is the software that loads a model’s weights and runs the model. The weights are the files that contain the model; the runner uses your computer’s memory and processing hardware to answer prompts. You can chat in the runner itself, or add a separate interface if you want one.
Local inference means the selected model processes the prompt on your computer. It does not mean that every service or feature in an app is local. Model searches and downloads need internet access, and a chat interface can connect to hosted models or cloud-based tools if you configure it to do so.
Check whether your computer is suitable
Hardware guidance depends on the runner, model, context size, and workload. LM Studio’s requirements page recommends 16 GB or more of RAM for Apple Silicon Macs and Windows systems. It says an 8 GB Mac may work with smaller models and modest context sizes. For Windows, LM Studio also recommends at least 4 GB of dedicated VRAM and requires AVX2 support for x64 systems. These are LM Studio recommendations, not universal requirements or performance guarantees for every local AI application. See LM Studio’s system requirements.
#1 Best Overall
- EVOLUTION AMD RYZEN AI MAX+ 395 MINI PC - GMKtec EVO-X2 is the next evolution in AI mini PC Ryzen Strix Halo series. Thanks to AMD Simultaneous Multithreading (SMT) the core-count is effectively doubled, to 32 threads. Ryzen AI Max+ 395 has 64 MB of L3 cache and can boost up to 5.1 GHz, depending on the workload. The Ryzen AI Max+ 395 is currently rated as the "most powerful x86 APU" on the market for AI computing.
- AI NPU with XDNA 2 ARCHITECTURE - Powered by 16 “Zen 5” CPU cores, 50+ peak AI TOPS XDNA 2 NPU and a truly massive integrated GPU driven by 40 AMD RDNA 3.5 CUs, the Ryzen AI MAX+ 395 is a transformative upgrade and delivers a significant performance boost over the competition. The Ryzen AI Max+ 395 excels in consumer AI workloads like the llama.cpp-powered application: LM Studio. Shaping up to be the must-have app for client LLM workloads, LM Studio allows users to locally run the latest language model without any technical knowledge required and unleash their creativity and productivity.
- AMD RADEON 8090S iGPU GAMING PC - The AMD Radeon RX 8060S offers all 40 CUs with up to 2.9 GHz graphics clock and uses the new RDNA 3.5 architecture. The powerful iGPU is positioned between an RTX 4060 and 4070 laptop GPU and therefore enables gaming in FHD at maximum details in most demanding games. The 8060S can also utilize the full 64GB pool, which is perfect for running LLMs such as Deepseek 32B, which runs comfortably on this machine.
- EIGHT CHANNEL LPDDR5X - LPDDR5X is a new ground breaking memory small form factor installed on-board. With blazing speeds up to to 8000MT/s, it runs 1.5x faster than the DDR5 SODIMMs; 90% better performance over DDR5 SODIMMs in video conferencing and photo editing; 30% better performance in productivity apps; 4% better performance in digital content workloads.
- QUAD SCREEN 8K DISPLAY SUPPORT - EVO-X2 AI Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and dual USB 4 40Gbps Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support.
- Mac: LM Studio supports Apple Silicon Macs running macOS 14.0 or newer; its current requirements page says Intel Macs are not supported.
- Windows: LM Studio supports x64 and Snapdragon X Elite ARM systems. Its x64 support requires AVX2.
- Linux: LM Studio lists x64 and ARM64 support, distributes an AppImage, and specifies Ubuntu 20.04 or newer.
These details apply to LM Studio, not all model runners. Ollama notes that speed depends on hardware and that large models can be slow without a strong GPU. If your computer has limited memory, start with a smaller model and test it on the task you actually want to do rather than assuming a particular model will run well.
Choose a model runner
| Option | How you install and use it | Finding and loading models | Interface |
|---|---|---|---|
| LM Studio | Guided desktop application; check its platform-specific requirements first. | Use Discover to find a model, download it, then load it from the Chat tab. | Chat is built into the app. |
| Ollama | Install from the official download page, using the instructions for your operating system. | Choose a model supported by Ollama and distinguish local models from cloud models hosted by Ollama. | You can use Ollama directly or connect an optional interface such as Open WebUI. |
For a first setup, LM Studio’s graphical workflow is straightforward if your computer meets its requirements. Choose Ollama if you are comfortable using a terminal or want its model server. Neither option is a universal speed or quality winner; results depend on the model, computer, and task.
Set up a first local chat in LM Studio
- Install the app. Download the current LM Studio version for your supported operating system and install it.
- Find a model. Open Discover, then search for or select a model. Check the model’s own license and usage terms before downloading; model weights can have different licenses, and “open-weight” does not necessarily mean “open source.”
- Download the model. The model’s weights must be available on your computer before it can run locally. LM Studio notes that weights are often distributed as
.ggufor.safetensorsfiles. - Load the model. Open the Chat tab and use its model loader to load the downloaded model. Loading allocates memory for the weights and other parameters.
- Try a simple prompt. Once the model is loaded, start a conversation. Test a small, representative task and adjust your model choice if the response is too slow or the model cannot handle the task.
LM Studio’s getting-started guide documents this workflow at Get started with LM Studio. There is no model that can be recommended as the best choice for every computer and task based on these documented requirements alone.
Rank #2
- 97 TOPS AI SUPERCHARGED PERFORMANCE – BUILT FOR THE AI ERA --- Powered by the next-gen Intel Core Ultra 5 226V processor (up to 4.50GHz) built on TSMC’s advanced 3nm N3B process, the K17 delivers an incredible 97 TOPS of total AI performance (40 TOPS NPU + 53 TOPS GPU). Unlike traditional systems that rely solely on CPU/GPU, this triple AI architecture enables real-time local AI processing, faster inference, and smoother multitasking—perfect for AI assistants, local LLMs, content generation, and intelligent workflows without cloud dependency.
- INTEL ARC 130V GRAPHICS – DISCRETE-CLASS POWER, NO GPU REQUIRED --- Experience next-level integrated graphics with the Intel Arc 130V GPU (up to 1.85GHz), delivering up to 53 TOPS AI compute and supporting hardware ray tracing, XeSS AI upscaling, and AV1 encoding. Compared to previous-gen iGPUs, performance is massively improved, enabling smooth AAA gaming, 4K video editing, and real-time rendering—bringing desktop-class graphics power into a compact, energy-efficient mini PC.
- DEDICATED NPU – TRUE LOCAL AI, FASTER & MORE SECURE --- Equipped with Intel AI Boost NPU delivering 40 TOPS of dedicated AI acceleration, the K17 handles AI workloads independently without consuming CPU/GPU resources. From AI noise cancellation and real-time translation to local model deployment and generative AI tasks, enjoy faster response times, lower power consumption, and enhanced data privacy with fully local processing.
- LPDDR5X 8533 MT/s HIGH-BANDWIDTH MEMORY – BUILT FOR HEAVY MULTITASKING --- Featuring 16GB LPDDR5X onboard memory running at blazing 8533MT/s, the K17 provides ultra-high bandwidth for demanding workloads. Compared to traditional DDR4 systems, it ensures faster data throughput, smoother multitasking, and stable large-model loading—ideal for AI applications, creative software, and multi-window productivity without lag.
- DUAL M.2 SSD (GEN5 + GEN4) EXPANSION – UP TO 16TB MASSIVE STORAGE --- Designed for power users, the K17 supports dual M.2 2280 SSD slots (PCIe Gen5×4 + Gen4×2), enabling up to 16TB total storage (8TB×2). Experience ultra-fast read/write speeds for massive datasets, AI model storage, and 4K/8K media files—no more external drives or storage limitations, everything stays fast and accessible.
Install Ollama instead
Ollama’s official download page provides an install command for macOS or Linux and a PowerShell command for Windows. Use the command for your operating system, then follow Ollama’s instructions to run a model. The commands below are copied from the vendor’s download page:
The Tool Desk
Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →- macOS or Linux:
curl -fsSL https://ollama.com/install.sh | sh - Windows PowerShell:
irm https://ollama.com/install.ps1 | iex
Ollama offers models that run locally as well as cloud models hosted by Ollama. Confirm which type you are selecting: choosing a cloud model does not keep its inference on your computer. See Download Ollama for current installation and model information.
Do you need a separate chat interface?
No. You can begin with the chat interface included in LM Studio or use Ollama without adding another interface. Open WebUI is an optional choice if you want a separate interface that connects to local model servers such as Ollama, or to hosted APIs.
Rank #3
- 【Low Power for Always-On AI Workflows】At just 15W TDP, the GEEKOM A7 uses far less power than a traditional 350W desktop, helping reduce electricity costs, heat, and cooling noise during extended operation. That efficiency makes it ideal for keeping cloud AI assistants and AI Agent tasks running in the background—automating document summaries, email polishing, meeting notes, content rewriting, research, and scheduled workflows throughout the day. The energy savings can help recoup the device cost in about 1 year, making A7 a practical choice for 24/7 AI task hosting and efficient everyday computing.
- 【Ryzen 7 7730U – More Than a Low-Power PC】Think low power means less performance? Not here. The Ryzen 7 7730U mini computer packs 8 cores, 16 threads, and up to 4.5GHz, giving you the power to handle multitasking, dozens of tabs, video calls, and creative work smoothly. AMD Radeon Graphics supports 4K playback, multi-display work, photo editing, and casual gaming without a dedicated GPU. Compared with the Ryzen 7 5825U and Ryzen 5 7430U, it delivers up to 20% higher performance for faster response and smoother everyday computing—all in a compact, energy-efficient Mini desktop.
- 【Lock In More Memory Before It Costs More】32GB gives you the headroom most demanding tasks need today—and room to grow tomorrow. Built for heavy multitasking, content creation, large projects, and AI-assisted workloads, the GEEKOM mini pc starts you with twice the memory of a typical 16GB setup, so you can skip an immediate upgrade. With AI driving greater demand for memory, starting with 32GB is a smarter way to stay ready for what’s next. The 500GB PCIe Gen4 x4 SSD delivers fast storage, with support for up to 64GB RAM and 4TB SSD storage when you need more.
- 【Premium Metal Design & 3-Year Warranty】Why settle for plastic? The GEEKOM mini desktop features a premium aluminum alloy chassis that resists daily wear and helps dissipate heat during extended use. Rigorous quality testing and CE, FCC, and RoHS compliance support dependable performance, backed by a 3-year limited warranty and professional support for long-term peace of mind.
- 【One Mini PC, All Your Ports】Stay connected with dual USB-C ports, 5 USB 3.2 ports, dual HDMI 2.0, and a 2.5G LAN port for fast, flexible connectivity. The USB-C ports support high-speed data transfer, display output, and peripheral power, while Wi-Fi 6E keeps streaming, file transfers, and online work fast and reliable. From multiple peripherals to high-resolution displays, everything you need stays within easy reach.
In Open WebUI, the endpoint selected for a conversation determines where inference takes place. Selecting a local model does not make a separately configured hosted provider, cloud tool, document-processing service, or embedding service local. If you compare local and hosted models, the same prompt may be sent to each selected endpoint. Check the provider and any auxiliary services configured for the conversation before entering sensitive information. Open WebUI explains provider connections in its Connect Local and Cloud Models guide.
Open WebUI’s quick-start guide describes different container images, but Docker and an additional interface are not necessary for the basic LM Studio or Ollama setup. Consider that route only if you specifically want Open WebUI or its extra capabilities; see its Quick Start.
Quick wins for a faster PC:
Clear out junk files and repair common Windows errorsFree Scan →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Does a local AI assistant work offline and keep data private?
After the model is downloaded, LM Studio says it can run entirely offline. Its documentation says that prompts entered while chatting with LLMs in LM Studio do not leave the device, and that documents added for chat or retrieval-augmented generation stay on the machine and are processed locally. Those are LM Studio’s claims about its local operation. Searching for models, downloading models or runtimes, retrieving model catalog details, and checking for app updates use network access. See LM Studio’s Offline Operation documentation.
Rank #4
- EVOLUTION AMD RYZEN AI MAX+ 395 MINI PC - GMKtec EVO-X2 is the next evolution in AI mini PC Ryzen Strix Halo series. Thanks to AMD Simultaneous Multithreading (SMT) the core-count is effectively doubled, to 32 threads. Ryzen AI Max+ 395 has 64 MB of L3 cache and can boost up to 5.1 GHz, depending on the workload. The Ryzen AI Max+ 395 is currently rated as the "most powerful x86 APU" on the market for AI computing.
- AI NPU with XDNA 2 ARCHITECTURE - Powered by 16 “Zen 5” CPU cores, 50+ peak AI TOPS XDNA 2 NPU and a truly massive integrated GPU driven by 40 AMD RDNA 3.5 CUs, the Ryzen AI MAX+ 395 is a transformative upgrade and delivers a significant performance boost over the competition. The Ryzen AI Max+ 395 excels in consumer AI workloads like the llama.cpp-powered application: LM Studio. Shaping up to be the must-have app for client LLM workloads, LM Studio allows users to locally run the latest language model without any technical knowledge required and unleash their creativity and productivity.
- AMD RADEON 8090S iGPU GAMING PC - The AMD Radeon RX 8060S offers all 40 CUs with up to 2.9 GHz graphics clock and uses the new RDNA 3.5 architecture. The powerful iGPU is positioned between an RTX 4060 and 4070 laptop GPU and therefore enables gaming in FHD at maximum details in most demanding games. The 8060S can also utilize the full 64GB pool, which is perfect for running LLMs such as Deepseek 32B, which runs comfortably on this machine.
- EIGHT CHANNEL LPDDR5X - LPDDR5X is a new ground breaking memory small form factor installed on-board. With blazing speeds up to to 8000MT/s, it runs 1.5x faster than the DDR5 SODIMMs; 90% better performance over DDR5 SODIMMs in video conferencing and photo editing; 30% better performance in productivity apps; 4% better performance in digital content workloads.
- QUAD SCREEN 8K DISPLAY SUPPORT - EVO-X2 AI Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and dual USB 4 40Gbps Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support.
Ollama’s FAQ says it does not see prompts or data when Ollama is run locally. Ollama also documents a local-only setting that disables its cloud features, including cloud models and web search. Its service binds to 127.0.0.1:11434 by default; changing the bind address can expose it beyond the default local interface, so do that only with suitable security configuration. See the Ollama FAQ.
Offline use and privacy therefore depend on the specific runner, model endpoint, and tools you select—not just on installing local software. If you handle sensitive material, verify that every provider and auxiliary service in the workflow is local or otherwise appropriate for that material.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
Recommended Free Tools
