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text model · DeepSeek-R1 · Android

Can I run DeepSeek R1 on Google Pixel 9 Pro?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. DeepSeek R1 needs ~383.7 GB even at Q4_K_M, but Google Pixel 9 Pro only has ~10.5 GB usable.

Needs ~383.7 GB Device usable ~10.5 GB

Needs ~383.7 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 373.2 GB: DeepSeek R1 needs roughly 383.7 GB at Q4_K_M and Google Pixel 9 Pro leaves only about 10.5 GB usable for a model. No single tracked device has enough memory; DeepSeek R1 needs a multi-GPU or high-memory rig.

Q4_K_M needed
~383.7 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
~288 GB
Q3_K_M
~335 GB
Q4_K_M
~383.7 GB
Q5_K_M
~485.1 GB
Q6_K
~557.2 GB
Q8_0
~671.3 GB
FP16
~1349 GB
The line marks Google Pixel 9 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 DeepSeek-R1
Parameters
671B (MoE, 37B active)
Q4_K_M size
376.65 GB
Q8_0 size
664.3 GB
Context
128k
Ollama tag
deepseek-r1:671b
Full DeepSeek R1 requirements →
Device Android
Memory
16 GB ram
Usable for weights
~10.5 GB
Best runtime
llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)
Best models for Google Pixel 9 Pro →

What you can run instead

FAQ

Can Google Pixel 9 Pro run DeepSeek R1?

No. DeepSeek R1 needs ~383.7 GB even at Q4_K_M, but Google Pixel 9 Pro only has ~10.5 GB usable.

How much memory does DeepSeek R1 need?

Google Pixel 9 Pro does not have enough memory. At Q4_K_M the weights are ~376.65 GB; with KV cache and runtime overhead, budget ~383.7 GB at a 4k context. It is a Mixture-of-Experts model (671B total / 37B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run DeepSeek R1 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.