The Tool Desk
Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Running an AI model locally means the model processes your request on a device or server you or your organization controls, rather than sending it to a third-party model service. That can reduce the amount of prompt content exposed to an outside provider, but “local” does not by itself mean private, secure, or offline. The key is to identify where inference happens and what the surrounding app still sends, saves, or exposes.
What “running locally” means
Inference is the step in which a model uses an input, such as a question or document, to produce an output. With on-device inference, that processing happens on the same device you use. With self-hosted inference, a model runs on a server controlled by you or your organization. In either case, the model is not necessarily operated by a third-party cloud provider.
As an Amazon Associate I earn from qualifying purchases.
The distinction matters: a self-hosted model server still receives prompts from client devices over a network. Its operator may control the server, but the request has left the device that created it. Microsoft’s Windows Server local inference guidance distinguishes embedded inference from shared endpoints and warns that local placement alone is not a security boundary.
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 problemsWhat local inference changes—and what it does not
If inference truly happens on your device, the prompt and response need not be sent to an external model provider for that inference. This can reduce exposure to that provider, but it does not guarantee that every part of the application stays on-device. Consider the whole data path, not just the model’s location.
#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 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.
- Network activity: Model downloads, catalog refreshes, software updates, diagnostics, usage metadata, synchronization, and cloud fallback may still use the internet.
- Local storage: Chat histories, retrieved documents, logs, temporary files, model files, and credentials may remain on the device or server. Someone who gains access to those systems may be able to access them.
- Application behavior: An app can process prompts locally but handle metadata or optional features differently. Read the app’s policy and settings rather than inferring its behavior from the model’s location.
- Model trust: Model files come from somewhere and may be subject to licensing, integrity, or security concerns. Use sources you trust and keep the runtime and its dependencies maintained.
For example, Microsoft says that Foundry Local inference inputs and outputs stay on-device after a model has been downloaded; initial model downloads require internet access, and catalog refreshes may occur. Those statements describe Foundry Local and Windows AI APIs, not every local AI application. See Microsoft’s Windows AI FAQ for its product-specific details.
Ollama’s March 2026 privacy policy likewise distinguishes locally processed prompt and response content from limited device and usage metadata, and treats cloud-hosted model use separately. That is a vendor’s description of its own software and services, not an independent audit or a rule for all local-model software.
Rank #2
- 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.
On-device, self-hosted, and cloud inference compared
| Consideration | On-device | Self-hosted server | Third-party cloud |
|---|---|---|---|
| Where inference happens | On the device running the app. | On a server operated by you or your organization; client prompts travel to it over a network. | On infrastructure operated by a service provider. |
| Prompt exposure | Can avoid sending inference content to an external model provider, subject to the app’s other data flows. | Prompts leave the client device, even if the server is under your control. | Requests go to the provider, so its access, retention, and contractual practices matter. |
| Security work | Protect the device, accounts, local files, and app settings. | Secure the server, endpoint, network, client access, secrets, model files, and logs. | The provider maintains its service infrastructure; customers still need to configure APIs and handle data securely. |
| Compute and scale | Limited by the device’s available resources and the workload. | Can use more capable hardware, but the operator must provision and maintain it. | Can offer scalable compute and larger models, subject to service availability and cost. |
| Connectivity | May work offline after setup, depending on the runtime and app. | Clients need network access to the server; the server may also need connectivity for setup or updates. | Requires connectivity to the service. |
Microsoft’s local and cloud AI comparison also identifies privacy and security, resource availability, maintenance, performance, scalability, connectivity, model size, and cost as factors to weigh. Local deployment shifts more operational responsibility to the user or organization; a hosted service generally handles more of its own infrastructure maintenance.
How to assess privacy and security before using a local model
- Map the data path. Find out where prompts, retrieved documents, outputs, model files, chat history, logs, and diagnostics are processed or stored. Ask whether data is synced or shared with other users.
- Check network behavior. Review whether setup, model downloads, catalog refreshes, updates, or telemetry contact external services. Test what happens when a model is unavailable: does the app wait, fail, or send the request to a cloud model?
- Review the app’s settings and policy. Look for controls for history, diagnostics, usage data, sync, and cloud features. A locally running model does not establish how its surrounding application handles these items.
- Protect a shared endpoint. Restrict network access to approved clients, authenticate and authorize users, use approved TLS to protect traffic, and store credentials in an approved secret store. Protect model files, logs, and temporary data as well.
- Maintain the system and model lifecycle. Keep the operating system and runtime current, monitor for vulnerabilities, and review where model files come from and which license applies. Microsoft notes that local deployments leave data security to the user and updates and vulnerability monitoring to the developer or operator.
- Review consequential outputs. Treat generated text, code, and commands as untrusted until checked. For decisions or actions with significant consequences, keep a human in the loop; review commands and code before allowing them to change system state.
When a cloud or hybrid option may be more appropriate
Cloud inference means sending a request to a provider’s service, so the provider’s data handling, access controls, retention practices, and applicable agreements become relevant. In return, a cloud service may provide access to scalable compute or larger models without requiring you to operate the infrastructure yourself.
Rank #3
- 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.
A hybrid app can use a local model when it is available and switch to a cloud model when the device cannot handle the task or the local model is unavailable. “Local first” therefore does not necessarily mean “local only.” Check whether fallback is automatic, what data it sends, and whether you can disable it or require confirmation.
Apple’s Private Cloud Compute is a cloud-processing comparison, not local inference. Apple says requests are encrypted to validated nodes and that user data is deleted after the response and unavailable to Apple staff. Those are claims about Apple’s own design and documentation; they should not be taken as a general description of cloud AI services.
Rank #4
- 【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.
What hardware do you need?
There is no universal computer specification implied by “local AI.” Requirements depend on the model and the work you expect it to do. Microsoft identifies CPU, GPU, NPU, memory, and storage as relevant device constraints; model architecture, parameter count, quantization, context length, concurrency, and latency targets also affect resource needs. Check the compatibility guidance for the specific runtime and model rather than choosing hardware based on a generic claim about local AI. Some optional local model downloads may be several gigabytes, but that is not a specification for every model.
Recommended Free Tools
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.
