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text model · Qwen3-VL · iOS

Can I run Qwen3-VL 4B on iPhone 16 Pro?

Compatibility verdict VRAM threshold engine
Yes, but tight slow on this hardware ~10 tok/s est.

Yes. Qwen3-VL 4B runs on iPhone 16 Pro at Q4_K_M (~4.4 GB of ~4.5 GB usable).

Needs ~4.4 GB Device usable ~4.5 GB

Fits at Q4_K_M (~4.4 GB of ~4.5 GB usable) but with little headroom. Close background apps, and expect slow generation on a phone.

That figure is at a 4k context and moves about ±15% as context length changes. iPhone 16 Pro leaves ~0.1 GB of headroom.

Q4_K_M needed
~4.4 GB
Usable on device
~4.5 GB
Device memory
8 GB
Best quant
Q4_K_M
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Which quant fits

Quant ladder vs ~4.5 GB usable
Q2_K
~3.2 GB
Q3_K_M
~3.5 GB
Q4_K_M
~4.4 GB
Q5_K_M
~4.5 GB
Q6_K
~4.9 GB
Q8_0
~6.1 GB
FP16
~10.2 GB
The line marks iPhone 16 Pro's ~4.5 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.
Power draw
~12 W
Electricity / 1M tokens
~$0.05
Pays for itself after
~2,220M tok

At ~$0.15/kWh and the estimated ~10 tok/s, a million generated tokens costs about $0.05 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$999 iPhone 16 Pro pays for itself after roughly 2,220 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.

How to run it

On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.).

Model Qwen3-VL
Parameters
4.44B
Q4_K_M size
3.11 GB
Q8_0 size
4.77 GB
Context
256k
Ollama tag
qwen3-vl:4b
Full Qwen3-VL 4B requirements →
Device iOS
Memory
8 GB unified
Usable for weights
~4.5 GB
Power draw
~12 W
Best runtime
llama.cpp + Metal (via PocketPal or Off Grid app)
Best models for iPhone 16 Pro →

You could also run

Run Qwen3-VL 4B on other hardware

Nvidia GeForce RTX 2060 (6GB)Apple M1 (8GB)8GB RAM Laptop (CPU/iGPU only)iPhone 15 ProiPhone 16Generic Android Phone (8GB RAM)

FAQ

Can iPhone 16 Pro run Qwen3-VL 4B?

Yes. Qwen3-VL 4B runs on iPhone 16 Pro at Q4_K_M (~4.4 GB of ~4.5 GB usable).

How much memory does Qwen3-VL 4B need?

It is a tight fit on iPhone 16 Pro. At Q4_K_M the weights are ~3.11 GB; with KV cache and runtime overhead, budget ~4.4 GB at a 4k context.

What is the best tool to run Qwen3-VL 4B 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.

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Sources

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.