text model · DeepSeek-V4 · iOS
Can I run DeepSeek-V4-Flash on iPhone 17?
No. DeepSeek-V4-Flash needs ~179.7 GB even at Q4_K_M, but iPhone 17 only has ~4.5 GB usable.
Needs ~179.7 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 175.2 GB: DeepSeek-V4-Flash needs roughly 179.7 GB at Q4_K_M and iPhone 17 leaves only about 4.5 GB usable for a model. The lightest tracked hardware that runs DeepSeek-V4-Flash is the Apple M3 Ultra (256GB) at 256 GB. See DeepSeek-V4-Flash on Apple M3 Ultra (256GB).
- Q4_K_M needed
- ~179.7 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
- 284B (MoE, 13B active)
- Q4_K_M size
- 174.87 GB
- Q8_0 size
- 302.27 GB
- Context
- 1000k
- Memory
- 8 GB unified
- Usable for weights
- ~4.5 GB
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
What you can run instead
Run DeepSeek-V4-Flash on other hardware
FAQ
Can iPhone 17 run DeepSeek-V4-Flash?
No. DeepSeek-V4-Flash needs ~179.7 GB even at Q4_K_M, but iPhone 17 only has ~4.5 GB usable.
How much memory does DeepSeek-V4-Flash need?
iPhone 17 does not have enough memory. At Q4_K_M the weights are ~174.87 GB; with KV cache and runtime overhead, budget ~179.7 GB at a 4k context. It is a Mixture-of-Experts model (284B total / 13B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run DeepSeek-V4-Flash 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
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/deepseek-v4-flash/iphone-17) Sources
- apple.com
- developer.apple.com
- en.wikipedia.org/wiki/Apple_A19
- en.wikipedia.org/wiki/IPhone_17
- enclaveai.app
- github.com/a-ghorbani
- github.com/google-ai-edge
- github.com/mainframecomputer
- huggingface.co/bartowski
- huggingface.co/deepseek-ai
- huggingface.co/teamblobfish
- layla-network.ai
- macrumors.com
- privatellm.app
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.