Quick wins for a faster PC:
Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →You can run an AI language model on your own computer by installing a model runner, downloading model weights, and loading them into memory. For a first chat, LM Studio offers a graphical Discover-to-Chat workflow; Ollama is an alternative with Windows, macOS, and Linux installers, plus a local API for applications. “Open-source” does not guarantee unrestricted use: check the specific model’s license before downloading or using it.
What you need before you start
A local AI setup has two separate parts: the runner, which loads the model and performs inference, and the model weights, which contain the trained model. Weights are commonly distributed in formats such as .gguf or .safetensors. The runner and model are not interchangeable, and the model’s size, license, and hardware needs depend on the specific download. LM Studio’s getting-started guide explains the distinction and notes that models vary in their licenses and degrees of openness.
| # | Preview | Product | Price | |
|---|---|---|---|---|
| 1 |
|
MINISFORUM MS-02 Ultra Workstation Mini PC, Intel Core Ultra 9 285HX (24C/24T, up to 5.5GHz), PCIe... | $1,659.00 | Buy on Amazon |
| 2 |
|
GMKtec EVO-X2 AI Mini PC Ryzen Al Max+ 395 Superchip 128GB LPDDR5X 2TB SSD | $3,649.99 | Buy on Amazon |
Check your computer’s requirements
Requirements depend on the runner and operating system. LM Studio currently recommends 16 GB or more of RAM on Apple Silicon Macs and Windows PCs; for Windows it also recommends at least 4 GB of dedicated VRAM. These are LM Studio recommendations, not universal minimums for every runner or model. Consult its system requirements for supported chips, operating systems, and architecture details.
- Mac with LM Studio: Apple Silicon M1, M2, M3, or M4 and macOS 14.0 or later are supported. LM Studio recommends at least 16 GB RAM; 8 GB may work with smaller models and modest context. Intel Macs are not currently supported.
- Windows with LM Studio: x64 and Snapdragon X Elite ARM are supported. The x64 version requires AVX2; LM Studio recommends at least 16 GB RAM and 4 GB dedicated VRAM.
- Linux with LM Studio: x64 and ARM64 are supported through an AppImage; Ubuntu 20.04 or later is required.
- Windows with Ollama: Ollama documents Windows 10 22H2 or later. GPU acceleration has additional driver and backend requirements; see its Windows documentation if you plan to use a GPU.
Allow enough disk space
Model files can be large. Ollama’s Windows documentation says downloaded models may occupy tens to hundreds of GB, depending on what you choose. Check a model’s download size and make sure you have room before starting. If you need to keep models on another drive, Ollama for Windows documents the OLLAMA_MODELS environment variable for changing the model directory.
What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
#1 Best Overall
- High-Performance AI Processor：The MS-02 Ultra features an Intel Core Ultra 9 285HX (24C/24T, up to 5.5 GHz, 13 TOPS NPU), delivering fast and efficient performance for AI inference, algorithm development, and media workloads. A PCIe x16 expansion slot supports desktop-class GPU upgrades for advanced model training and accelerated computing tasks. It's ideal for creators, engineers, and teams handling intensive parallel workloads.
- 4 × M.2 PCIe 4.0 + 4 × DDR5 SODIMM slots:Four DDR5 SODIMM slots support up to 256 GB of memory, while ECC helps maintain data integrity in mission-critical environments. Four PCIe 4.0 M.2 slots support up to 24 TB of storage, supporting RAID 0/1/5/10, combining high-speed performance with data protection. It allows for the creation of independent scratch disks, media libraries, and project drives, providing high-throughput for production workflows.
- PCIe & USB 4.0 v2: Up to three PCIe slots can be equipped, including a dual-slot x16 GPU. The main slot supports PCIe 5.0, meeting the needs of high-bandwidth creative and computing workloads. USB 4.0 v2 (80Gbps) supports high-bandwidth external storage and displays.
- Ultra-fast Networking: Wi-Fi 7 further enhances wireless performance with next-generation speeds and low-latency stability. Intelligent bandwidth switching optimizes throughput in different network environments, ensuring optimal performance for enterprise or local networks. Dual 25GbE ports (providing up to approximately 3.125 GB/s bandwidth, about 25 times faster than traditional 1GbE), enabling seamless large-scale file transfers and parallel computing. 10GbE and 2.5GbE ports, with support for Intel vPro technology, ensure enterprise-grade remote management and deployment flexibility.
- Server-grade thermal architecture: Utilizing a dedicated CPU/GPU airflow design, equipped with a 6-pipe dual-fan cooler, it maintains stable performance even under sustained loads, delivering up to 140W Turbo power while maintaining a 100W TDP, and operating with noise levels as low as 36 dB. An integrated 350W power supply ensures stable and reliable output for demanding computing tasks and fully loaded extended configurations.
Run your first model with LM Studio
LM Studio is a straightforward choice if you want to find a model, download it, load it, and chat using a graphical interface. The steps below follow its documented workflow.
- Verify compatibility. Check your computer against LM Studio’s current system requirements.
- Install LM Studio. Download the current app from the official LM Studio guide.
- Find and download a model. Open Discover, choose a curated model or search for one, then download its weights. Review the model card and license before using it.
- Load the model. Open Chat and use the model loader to select the downloaded model. Loading allocates memory for its weights and other parameters, so a model that is too demanding for your computer may not load successfully.
- Start chatting. Once the model is loaded, enter a prompt in Chat and begin the conversation.
Use Ollama instead
Ollama provides installation options for Windows, macOS, and Linux. Its official download page displays the current installers and platform-specific instructions; use that page rather than relying on commands copied from older tutorials.
On Windows, Ollama can be used as an application or from Command Prompt or PowerShell. Its local API is available at http://localhost:11434, which is useful if you want an application to connect to Ollama; it is not necessary for a first interactive chat. See the Ollama for Windows documentation for Windows support, model storage, GPU prerequisites, and API details.
Know what the context setting means
Ollama’s FAQ documents a default context window of 4096 tokens and options for changing it. Context length is how much text the model can use in a conversation at a time; it is not the model file’s size. Increasing context can increase memory use, so leave it at the default unless you have a reason to change it and enough available memory. See the Ollama FAQ for the current setting options.
Rank #2
- EVOLUTION 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 128GB pool, which is perfect for running LLMs such as Deepseek 70B Q8, 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; 12% 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.
Choose a runner based on how you want to work
| What matters | LM Studio | Ollama |
|---|---|---|
| First use | Documented graphical flow: Discover, download, Chat/model loader, load, and chat. | Install through the official platform-specific instructions; supports application and command-line use. |
| Platforms and hardware | Check the current OS, architecture, and hardware requirements for your computer. | Installers are offered for Windows, macOS, and Linux; acceleration depends on platform and compatible drivers or backends. |
| Application integration | The documented beginner path focuses on interactive chat. | A local API is documented at http://localhost:11434 on Windows. |
The official setup documentation does not establish a universal speed or quality winner. Performance depends on the exact computer and model; large models can be slow on systems without a strong GPU. Choose by workflow and compatibility rather than assuming that one runner is always faster or better.
Understand licenses and local trade-offs
Downloading weights does not by itself mean a model is open source in the strict sense or that every use is permitted. Licenses and restrictions vary by model. Read the selected model’s license and usage terms, especially before commercial use. The LM Studio guide explicitly warns that models differ in license and degree of openness.
Running inference locally means the model is loaded and used on your computer through the chosen runner, but the setup still depends on local storage, memory, and compatible hardware. The published setup guidance does not establish a universal RAM formula, model-quality ranking, or speed benchmark; results vary with the model and machine. The LM Studio and Ollama requirements cited here are living product documentation, accessed October 4, 2026, and may change.
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.
