> ## Documentation Index > Fetch the complete documentation index at: https://docs.alpha.isaree.ai/llms.txt > Use this file to discover all available pages before exploring further. # Choose a model > Set your device in the Community Hub's model picker, read the fit badges, and understand why the recommendations look conservative. Picking an on-device model used to mean juggling parameter counts, [quantization](/concepts/quantization) levels, and RAM tables. The model picker on the [Community Hub](https://alpha.isaree.ai/en/community) now does that work for you: tell it which device you use, and it shows what actually runs well on it. This guide shows how to use the picker and explains the reasoning behind its recommendations — including why they look conservative. ## Set your device once When you pick a model while [building an Agent](/hub/build-agent) or a [Scribe Agent](/hub/build-scribe-agent), the picker asks which device you use — iPhone, iPad, or Mac. Every recommendation then tailors to it: * Each model shows how much [RAM](/concepts/ram-device-memory) it needs and a **fits your device** badge. Models that fit float to the top; ones that don't are dimmed. * [LLMs and VLMs](/concepts/llms-vlms) live in one unified list — no tab-hopping. * Start typing to search Hugging Face directly. Results show the organization, task, license, and usage stats inline, and carry the same **Runs / Needs X GB** badge as the curated models. ## What the badge guarantees The RAM number next to a model means *runs well*, not *barely loads*. A model that fits your device is guaranteed three things: * **A full 8K-token [context window](/concepts/context-window)** — enough working memory to get through a real session. * **The model runs solo** — Isa never stacks multiple models in memory at once. * **Headroom for the operating system** — enough margin that iOS won't force-quit Isa mid-session. The last one surprises people: an "8 GB" iPhone gives an app only about 4.8 GB of usable memory before iOS starts force-quitting it. The picker budgets against what's actually available, not the number on the box. ## Why the recommendations look conservative You might see a \~3 GB model asking for a 12 GB iPhone and think something's off. It's not — the context window drives the RAM number, not the weights. Here is the same model, Qwen 3.5 4B (about 3 GB on disk), under three different context guarantees: | Context guarantee | Peak memory | Needs | | :---------------- | :---------- | :----------------------------- | | 2K tokens | \~4.3 GB | 8 GB — iPhone 15 Pro / 16 / 17 | | 8K tokens | \~5.2 GB | 12 GB — iPhone 17 Pro / 17 Air | | 32K tokens | \~8.8 GB | 16 GB — iPad Pro only | The weights stay the same size; what grows is the model's working memory — every extra token of context needs more RAM to keep track of. The picker guarantees 8K tokens because that's what a real session needs. Promising 2K would make the requirements look friendlier, but a longer consultation would run out of memory and crash mid-visit. That's the philosophy behind the picker: the best model is the one that runs well on your device — fast and reliable — not the biggest one that technically loads. ## What fits which device The picker is the source of truth — set your device and read the badges. As a rough map of where things land today: | RAM | Devices | Recommended model | | :---- | :------------------------------------------- | :------------------------------------- | | 4 GB | iPhone 13, iPhone SE (3rd gen) | Qwen 3 1.7B | | 6 GB | iPhone 13 Pro, iPhone 14, iPhone 15 | Qwen 3.5 2B (vision) | | 8 GB | iPhone 15 Pro, iPhone 16 / 16 Pro, iPhone 17 | Qwen 3 4B, at a shorter context window | | 12 GB | iPhone 17 Air, iPhone 17 Pro / Pro Max | Qwen 3.5 4B, at the full 8K (vision) | iPads and Apple Silicon Macs ship with more RAM — 16 GB and up is common — so larger variants and longer context windows fit there. The picker covers the latest iPhones, iPads, and Macs. ## If nothing fits If your device can't run the model you need, there are two ways out: * **Move the Primary Agent to the cloud.** A [cloud model](/isa/primary-agent#pick-a-cloud-primary-agent) doesn't consume device RAM — you bring your own API key, and data leaves the device. See [On-device vs. cloud](/concepts/on-device-vs-cloud). * **Use Isa on a Mac.** Macs have the most usable memory of the supported devices — see [Hardware requirements](/help/hardware-requirements). Agents remain [on-device](/concepts/on-device-vs-cloud) only, so they always need a model that fits. ## Next Put the picker to work — build and publish an Agent on the Community Hub. Why RAM is the constraint that decides which models your device can run. How a 4B-parameter model fits in about 3 GB.