text model · Qwen3-Coder · Android

Can I run Qwen3-Coder 480B-A35B Instruct on Google Pixel 10 Pro?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Qwen3-Coder 480B-A35B Instruct needs ~276.2 GB even at Q4_K_M, but Google Pixel 10 Pro only has ~10.5 GB usable.

Needs ~276.2 GB Device usable ~10.5 GB

Needs ~276.2 GB even at Q4_K_M, but only ~10.5 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 265.7 GB: Qwen3-Coder 480B-A35B Instruct needs roughly 276.2 GB at Q4_K_M and Google Pixel 10 Pro leaves only about 10.5 GB usable for a model. No single tracked device has enough memory; Qwen3-Coder 480B-A35B Instruct needs a multi-GPU or high-memory rig.

Q4_K_M needed: ~276.2 GB
Usable on device: ~10.5 GB
Device memory: 16 GB

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Which quant fits

Quant ladder vs ~10.5 GB usable

Q2_K

~207.1 GB

Q3_K_M

~240.7 GB

Q4_K_M

~276.2 GB

Q5_K_M

~348.1 GB

Q6_K

~399.7 GB

Q8_0

~481.4 GB

FP16

~966.1 GB

The line marks Google Pixel 10 Pro's ~10.5 GB budget; rungs past it are too large.

How to run it

On Android use PocketPal AI (Polished app, download GGUF and run offline.).

Model Qwen3-Coder

Parameters: 480B (MoE, 35B active)
Q4_K_M size: 270.14 GB
Q8_0 size: 475.3 GB
Context: 256k
Ollama tag: qwen3-coder:480b

Full Qwen3-Coder 480B-A35B Instruct requirements →

Device Android

Memory: 16 GB ram
Usable for weights: ~10.5 GB
Power draw: ~7 W
Best runtime: llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)

Best models for Google Pixel 10 Pro →

What you can run instead

FAQ

Can Google Pixel 10 Pro run Qwen3-Coder 480B-A35B Instruct?

No. Qwen3-Coder 480B-A35B Instruct needs ~276.2 GB even at Q4_K_M, but Google Pixel 10 Pro only has ~10.5 GB usable.

How much memory does Qwen3-Coder 480B-A35B Instruct need?

Google Pixel 10 Pro does not have enough memory. At Q4_K_M the weights are ~270.14 GB; with KV cache and runtime overhead, budget ~276.2 GB at a 4k context. It is a Mixture-of-Experts model (480B total / 35B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Qwen3-Coder 480B-A35B Instruct on Android?

On Android, PocketPal AI (Polished app, download GGUF and run offline.) is the go-to option. NPU acceleration is limited and chip-specific; most apps run on CPU. Expect 1B-4B class.

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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.