text model · Qwen2.5-Coder · iOS
Can I run Qwen2.5 Coder 32B on iPhone 15 Pro?
No. Qwen2.5 Coder 32B needs ~20.7 GB even at Q4_K_M, but iPhone 15 Pro only has ~4.5 GB usable.
Needs ~20.7 GB even at Q4_K_M, but only ~4.5 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 16.2 GB: Qwen2.5 Coder 32B needs roughly 20.7 GB at Q4_K_M and iPhone 15 Pro leaves only about 4.5 GB usable for a model. The lightest tracked hardware that runs Qwen2.5 Coder 32B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Qwen2.5 Coder 32B on Nvidia GeForce RTX 4090 (24GB).
- Q4_K_M needed
- ~20.7 GB
- Usable on device
- ~4.5 GB
- Device memory
- 8 GB
Which quant fits
How to run it
On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.).
- Parameters
- 32B
- Q4_K_M size
- 18.49 GB
- Q8_0 size
- 32.43 GB
- Context
- 32k
- Ollama tag
- qwen2.5-coder:32b
- Memory
- 8 GB unified
- Usable for weights
- ~4.5 GB
- Power draw
- ~14 W
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
What you can run instead
Run Qwen2.5 Coder 32B on other hardware
FAQ
Can iPhone 15 Pro run Qwen2.5 Coder 32B?
No. Qwen2.5 Coder 32B needs ~20.7 GB even at Q4_K_M, but iPhone 15 Pro only has ~4.5 GB usable.
How much memory does Qwen2.5 Coder 32B need?
iPhone 15 Pro does not have enough memory. At Q4_K_M the weights are ~18.49 GB; with KV cache and runtime overhead, budget ~20.7 GB at a 4k context.
What is the best tool to run Qwen2.5 Coder 32B on iOS?
On iPhone and iPad, Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.) is the standard choice. Phones realistically run 1B-4B class models. Anything larger thermally throttles or OOMs.
Embed this
[](https://localmodel.run/can-i-run/qwen2.5-coder-32b/iphone-15-pro) Sources
- cpu-monkey.com
- developer.apple.com
- enclaveai.app
- forums.macrumors.com
- github.com/a-ghorbani
- github.com/google-ai-edge
- github.com/mainframecomputer
- gsmarena.com
- helloexpress.net
- huggingface.co/bartowski
- huggingface.co/Qwen
- layla-network.ai
- ollama.com/library/qwen2.5-coder
- ollama.com/library/qwen2.5-coder/tags
- privatellm.app
- support.apple.com
- techinsights.com
- wccftech.com
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.