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Yes, many PCs can run AI models locally. Whether yours can depends on its memory, processor and graphics support, operating system, and the model you choose. A phone can also connect to a model running on your PC, but that is remote access—not the phone running the model itself. Requirements for running a model directly on a phone are not established by the sources cited here.
What “running AI locally” means
With local inference, model files are stored on your computer and the model uses that device’s resources to generate responses. For example, LM Studio describes model weights distributed in GGUF or safetensors formats. Loading a model allocates memory for its weights and other parameters, so the model and its context size affect what your computer can handle.
Local execution is different from using a cloud-hosted AI service, and also different from opening an app on your phone that connects to a model hosted on your computer. The latter still depends on the computer to run the model.
How much memory do you need?
There is no universal RAM or VRAM threshold for local AI: requirements vary by runtime, model, and context size. LM Studio’s published figures are recommendations for that software, not guarantees of compatibility, speed, or performance for every model.
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| Computer and LM Studio support | Published requirements or recommendations |
|---|---|
| Windows | At least 16 GB RAM and 4 GB dedicated VRAM recommended; x64 systems require AVX2. Snapdragon X Elite ARM systems are listed as supported. |
| Apple Silicon Mac | M1, M2, M3, and M4 with macOS 14 or newer are listed; 16 GB or more RAM recommended. An 8 GB Mac may work with smaller models and modest context sizes. Intel Macs are unsupported. |
| Linux | x64 and ARM64 are listed; Ubuntu 20.04 or newer is specified. |
These figures come from the LM Studio System Requirements page, accessed in 2026. They are not independent benchmark results. Meeting a recommendation does not establish how quickly a particular model will respond or what answer quality it will provide.
Check your computer before choosing a model
- Operating system and processor: Confirm your operating system version, CPU architecture, and any required instruction support such as AVX2.
- Available memory: Check system or unified memory, and dedicated VRAM where applicable. Memory capacity alone is not a complete compatibility test.
- Model and context: Identify the specific model and context size you plan to use; both affect memory demand.
- Runtime support: Verify the current requirements for the software you intend to use. LM Studio’s list does not define what every runtime supports.
- Upgrade compatibility: If considering more RAM, first check your exact computer or motherboard, supported memory type, capacity limit, and available slots. A smaller model may work on hardware you already own.
One desktop setup route: LM Studio
LM Studio’s documented beginner workflow is to check compatibility, install the app, download model weights, load a model into memory, and chat. Its getting-started documentation covers that workflow.
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- Check whether your computer meets the system requirements for your operating system and processor.
- Install LM Studio using its official instructions.
- Download model weights in a format supported by the app, such as GGUF or safetensors.
- Load the model into memory, taking its size and intended context into account.
- Start a chat and assess whether the setup is usable for your needs.
Can your phone run a model locally?
The information cited here does not establish general minimum specifications for running a language model entirely on an iPhone or Android phone. A phone app’s ability to reach a model is not proof that the phone is executing it.
Using an iPhone to reach a PC-hosted model
LM Studio says its LM Link feature can connect an iPhone to a model hosted on a more powerful computer. The computer does the inference; the iPhone provides a way to access it. LM Studio describes the cross-device connection as end-to-end encrypted, but that does not change where the model runs. See LM Link documentation for the vendor’s description.
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Using an Android phone with a computer-hosted model
Android Studio’s documentation describes choosing a local model running on a personal computer to power IDE assistance, with a provider such as LM Studio or Ollama. That is evidence of a computer-hosted setup, not proof that a typical Android phone can run arbitrary language models itself. The relevant Android Studio documentation concerns that computer-based workflow.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why one model can need much more memory than another
Model size and context size change the resources a setup needs. For a dated, specific example, Ollama’s March 30, 2026 announcement of its Apple Silicon MLX support in preview highlighted a Qwen3.5-35B-A3B configuration and called for a Mac with more than 32 GB of unified memory for that featured setup. That figure applies to the announced configuration; it is not a general minimum for smaller models or all Ollama use. Check the Ollama MLX announcement for its scope and preview status.
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What local use does—and does not—tell you
Running a model on your own computer means that model inference occurs on that computer. If your phone connects to a host computer, the model still runs on the host. The sources cited here do not establish that local models match a particular hosted service in speed or answer quality, nor do they provide directly comparable PC-versus-phone benchmarks. Do not treat the word “local” alone as a guarantee about every part of an app’s data handling.
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