Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsiTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
You can run a chatbot on your own computer by installing a model runner, downloading compatible model weights, and starting a chat. For the simplest command-line setup, use Ollama; for a graphical app, use LM Studio. Choose llama.cpp if you want more control or a local server and are comfortable with manual configuration. The model runs on your computer, but you need to download its files before first use.
Choose the setup that fits how you want to work
| Your priority | Good starting point | What to expect |
|---|---|---|
| Few setup steps and a terminal is fine | Ollama | Install the app, run a model command, and chat in the terminal. The first run downloads the model. |
| A graphical interface | LM Studio | Find a model in Discover, load it in Chat, then start a conversation. |
| A local API or more configuration | llama.cpp | Run a GGUF model from the command line or start a local server. Setup and hardware configuration are more hands-on. |
These are workflow distinctions, not a performance ranking: the available documentation does not establish which tool is universally fastest, most private, or produces the best answers.
Check your computer before downloading a model
A model runner is the software that loads and runs a model; it is separate from the model’s downloaded weights. The model’s file size, quantization, context size, and hardware acceleration all affect how much memory it needs. Check the model’s download size and the current requirements for your operating system before you start.
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Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →A concrete Ollama example
Ollama’s 2026 Quickstart lists its Gemma 4 E2B example download at about 7.2 GB and recommends 8 GB of available VRAM, or unified memory on a Mac, for that example. These are figures for this particular model, not a minimum for every local chatbot. Larger context windows require more memory; when VRAM is insufficient, Ollama may use system RAM, which can make responses slower. See Ollama’s Quickstart.
#1 Best Overall
- 【High-Performance APU】The MS-S1 MAX features an AMD Ryzen AI Max+ 395 APU, integrating a Zen 5 architecture CPU (up to 5.1GHz, 16C/32T, 64M L3 Cache), an RDNA 3.5 GPU, and an NPU (50 TOPS). The total system output is 126 TOPS. It provides powerful parallel computing capabilities for demanding AI workflows. It is ideal for running local LLMs, multimodal models, and computationally intensive tasks
- 【128GB UMA Memory】Equipped with up to 128GB of LPDDR5x-8000MT/s unified memory, it enables the CPU and GPU to access a shared, high-bandwidth memory pool with extremely low latency. Ideal for large-scale AI inference, 3D workloads, and complex timelines in video editing. It eliminates traditional VRAM bottlenecks, ensuring smoother data transfer during high-intensity computations. The UMA design maximizes performance stability under high loads
- 【Flexible Expansion】The MS-S1 MAX features USB4 V2 (up to 80Gbps), dual 10GbE LAN, HDMI 2.1 (up to 8K60), a full-length PCIe x16 expansion slot, and dual M.2 slots supporting up to 16TB RAID 0/1. Wi-Fi 7 provides stronger signal coverage and a more stable wireless experience. The slide-out design facilitates upgrades and maintenance. It easily adapts to personal, studio, or rack-mount enterprise environments
- 【High-Efficiency Cooling System】Utilizing an aerospace-grade aluminum alloy chassis, copper base plate, six heat pipes, dual turbine fans, and advanced PCM thermal conductive material, it maintains stable cooling performance even under continuous load. This system supports 130W continuous power and 160W peak power operation, with a built-in 320W power supply. It boasts multiple global certifications including CCC, FCC, UL, CE, and UKCA, ensuring stable and reliable operation in various environments
- 【Cluster Design】Two MS-S1 MAX units can be configured as a dual-unit cluster to run a large 235B Q4 model locally, achieving an output speed of 10.87 tok/s. Supporting 2U rack deployment, multiple MS-S1 MAX units can be cascaded into a distributed cluster to create a high-efficiency AI computing center. A cluster of four MS-S1 MAX units successfully ran a DeepSeek-R1 671B Q4 large model. A reserved cluster power-on interface allows for unified start-up and shutdown
LM Studio’s platform guidance
LM Studio’s published requirements are specific to LM Studio and should not be treated as requirements for Ollama, llama.cpp, or every model. Its current guidance is:
- macOS: Apple Silicon M1, M2, M3, or M4 with macOS 14 or newer. At least 16 GB of RAM is recommended. Macs with 8 GB may work with smaller models and modest context sizes; Intel Macs are not currently supported.
- Windows: x64 and Snapdragon X Elite ARM are supported. AVX2 is required for x64; 16 GB of RAM and 4 GB of dedicated VRAM are recommended.
- Linux: x64 and ARM64 are supported. The listed distribution is AppImage, with Ubuntu 20.04 or newer; newer Ubuntu versions are described as not well tested.
Consult the LM Studio system requirements for the latest platform details.
Rank #2
- Built for Local AI and Advanced Workflows – The BOSGAME M5 AI Mini PC is powered by AMD Ryzen AI Max+ 395 with 16 cores, 32 threads, up to 5.1GHz, 50 TOPS NPU performance and up to 126 TOPS total AI performance. It is designed for local AI inference, private AI assistants, coding, data analysis, virtualization, content creation and demanding multitasking while keeping sensitive data on the device.
- 128GB Unified Memory for Large Models and Creative Projects – M5 includes 128GB LPDDR5X-8000 unified memory, giving the CPU and Radeon 8060S graphics access to a large shared memory pool. This helps support memory-intensive AI workloads, large project files, multiple virtual machines, 3D work, video editing and complex professional applications without the capacity limits of typical 32GB or 64GB mini computers.
- Radeon 8060S Graphics for Creation, Rendering and Gaming – Integrated Radeon 8060S graphics with 40 RDNA 3.5 compute units delivers high-end visual performance without a separate graphics card. Use the M5 creator workstation for 4K video editing, 3D rendering, CAD, AI image workflows, high-resolution media and modern gaming, while maintaining a compact desktop footprint.
- 2TB PCIe 4.0 SSD and Flexible Expansion – A pre-installed 2TB NVMe PCIe 4.0 SSD provides fast access to models, datasets, media libraries and project files. A second M.2 2280 PCIe 4.0 slot allows additional storage expansion, while the SD 4.0 card reader supports efficient photo and video workflows for creators and production teams.
- Professional Connectivity and Four-Display Support – Dual USB4 ports, HDMI 2.1 and DisplayPort 1.4 support up to four displays and resolutions up to 8K@60Hz. WiFi 7, Bluetooth 5.4 and 2.5GbE deliver fast networking for cloud collaboration, NAS access and business deployment. Windows 11 Pro, performance-mode switching, Wake-on-LAN and auto power-on support flexible workstation use.
GPU support depends on the device and software stack
Do not assume that any GPU will accelerate a model. Ollama documents different conditions for NVIDIA, AMD, Apple, and Vulkan-enabled hardware; support can depend on the GPU, operating system, drivers, and backend. Check Ollama’s hardware support page for your exact setup.
What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
Run a chatbot with Ollama
Ollama supports macOS, Windows, and Linux. Its Quickstart uses Gemma 4 E2B as an example; the command downloads that model if needed and opens a chat.
Rank #3
- Built for Local AI Development: AMD Ryzen AI Halo is designed for local AI development and inference, featuring 128GB unified memory and support for up to 200B parameter models to build and run intensive AI workloads locally.
- 128GB Unified Memory: Features 128GB LPDDR5x unified memory at 8000 MT/s with 256 GB/s memory bandwidth, providing a shared memory pool across the CPU, GPU, and NPU to support larger AI models.
- AMD Ryzen AI Max+ 395 Processor: Features 16 cores, 32 threads, and Zen 5 architecture, paired with AMD Radeon 8060S integrated graphics featuring 40 RDNA 3.5 compute units and an AMD XDNA 2 NPU with up to 50 TOPS.
- Linux AI Developer Platform: Purpose-built for Linux-based AI development with full AMD ROCm software support and preloaded tools, models, and workflows optimized for local AI development.
- Compact, Connected Design: Includes a 2TB M.2 SSD, 10GbE LAN, Wi-Fi 7, Bluetooth 5.4, USB-C connectivity, and HDMI 2.1b.
- Install Ollama for your operating system from its official download page, linked from the Quickstart.
- Open a terminal and run
ollama run gemma4:e2b. - Wait for the model download and startup, then type a message at the chat prompt.
- Enter
/byeto exit the chat.
Use the model name shown in the current Ollama documentation or library if you want a different model. Check its size, compatibility, and license before downloading. Ollama also offers a local API if you want to connect the model to another application; the Quickstart links to its API documentation.
Use LM Studio without a terminal
LM Studio’s basic workflow is to obtain a model, load it into memory, and chat. Loading allocates memory for the model weights and related parameters. Models are commonly distributed in formats such as GGUF or Safetensors.
Rank #4
- Unlock next-generation AI computing with AMD Ryzen AI Max+ 395 processor featuring 16 cores, 32 threads, up to 5.1GHz boost clock, and integrated Ryzen AI engine delivering up to 126 TOPS AI performance. EVO-X3 is designed for local AI models, content creation, development, and professional workloads.
- OCuLink External GPU Expansion – Upgrade Beyond a Mini PC: Take your graphics performance further with a dedicated OCuLink (PCIe 4.0 x4) interface. Connect an external GPU dock to add desktop-class graphics power for AAA gaming, AI acceleration, 3D rendering, video production, and advanced creative applications. EVO-X3 gives you the flexibility of a compact PC with workstation-level expansion capability.
- 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.
- Install the latest LM Studio version for a supported operating system, after checking the requirements above.
- Open the app’s Discover tab and select a model to download.
- Open the Chat tab and load the downloaded model.
- When loading completes, enter a message to begin chatting.
Model access, supported formats, and licenses differ. LM Studio advises users to make sure they can access the weights; read the selected model’s own terms for your intended use. See LM Studio’s getting-started guide.
Crashes, No Sound, or Screen Glitches?
Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteWindows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallUse llama.cpp for a command-line workflow or local server
llama.cpp is a more configurable option for people comfortable with command-line tools and hardware settings. It supports installation through package managers, Docker, prebuilt binaries, or a source build. Its documented examples use GGUF models and include running a model with llama-cli -m my_model.gguf, downloading a supported model with -hf, or launching a server with llama-server.
Best Value
- 【Leading AI Mini Workstation】MINISFORUM AI MS-S1 Max Workstation comes with AMD Ryzen AI Max+ 395 processor, which uses AMD's latest generation Zen 5 architecture. It has 16 Cores and 32 Threads, the boost clock is up to 5.1GHz. The overall processor performance is up to 126 TOPS, and the NPU performance reaches up to 50 TOPS. AMD Ryzen AI enables improved productivity, advanced collaboration, and improved efficiency.
- 【AMD Radeon 8060S Graphics 】The MS-S1 Max Mini PC equipped with AMD Radeon 8060S Graphics which built on the new generation of RDNA 3.5 architecture AMD graphics, it brings ultra-high frame rate experiences and advanced content creation features anywhere and delivers staggering performance. It can handle all your computing and multimedia tasks efficiently.
- 【Five 8K Video Output】This MS-S1 Max Workstation comes with five video outputs, 1x HDMI (8K@60Hz), 2x USB4(40Gbps,Alt DP2.0,PD out 15W) and 2x USB4 V2(80Gbps,Alt DP2.0,PD out 15W) Outputs, which support multiple monitors display at the same time and provide a larger and wider filed of view and improve your work efficiency. It is used in fields that require high-performance computing and graphics processing, including digital signage and securities trading, as well as work that uses CAD, such as engineering design, scientific calculations, animation production, and post-production for movies and television
- 【 Fast and Stable Wire & Wireless Speed】It comes with Two 10G Lan Ports for wired connection and and Wi-Fi 7 / BT5.4 for wireless connection, which increased the network speed greatly and expand its functions and improved performance of computer to a large extent and allows you to use more networks such as software routers (OpenWRT / DD-WRT / Tomato etc.), firewalls, NAT, network isolation etc.
- 【Large Storage & Flexible Expandability】This Workstation equipped with 64GB LPDDR5-8000MHz + 2TB M.2 2280 PCIe4.0 SSD. There is another PCIe4.0 SSD slot available for up to 8TB, these SSD slots are compatible with RAID0 and RAID1, you can store movies, videos, photos, important files easily. What’s more, it also comes with 1x standard PCIex16 slot(PCIe4.0x4) inside.
The server provides a basic browser interface on localhost and an OpenAI-compatible endpoint. The project documents CPU and GPU backends, quantization options, and hybrid CPU/GPU inference, but selecting a compatible build and configuration takes more work than the app-based routes. Start with the llama.cpp project documentation.
Plan for offline use
“Local” does not mean you can skip the initial downloads: you need the runner and model files on your computer first. LM Studio documents that, once the files are present, its chat, document chat, and local server can work without an internet connection. See LM Studio’s offline-operation guide. Offline capability does not by itself establish a full privacy or security guarantee; consider what data you enter and which other applications or services you connect.
Quick Recap
If the model will not load or runs slowly
- It fails to load: Check that the model format is supported by your runner and that your computer has enough available memory for the selected model and context size.
- The first run takes time: The model files must be downloaded before they can be loaded. Confirm that the download completed and that you have enough storage.
- Responses are slow: The model may exceed available GPU memory and use system RAM, or your hardware may not be accelerated by the configured backend. Check the runner’s hardware documentation and consider a smaller model or context.
- You cannot use a model for a planned purpose: Review that model’s license and access terms. Licenses and degrees of openness vary by model.
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.
Free tools Windows power users keep installed
One-click scans. No signup required.
