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text model · Qwen3.6 · Android

Can I run Qwen3.6 35B-A3B on Samsung Galaxy S26 Ultra (16GB, 1TB config)?

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

No. Qwen3.6 35B-A3B needs ~24.5 GB even at Q4_K_M, but Samsung Galaxy S26 Ultra (16GB, 1TB config) only has ~12 GB usable.

Needs ~24.5 GB Device usable ~12 GB

Needs ~24.5 GB even at Q4_K_M, but only ~12 GB is usable.

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

The gap is about 12.5 GB: Qwen3.6 35B-A3B needs roughly 24.5 GB at Q4_K_M and Samsung Galaxy S26 Ultra (16GB, 1TB config) leaves only about 12 GB usable for a model. The lightest tracked hardware that runs Qwen3.6 35B-A3B is the Nvidia GeForce RTX 5090 (32GB) at 32 GB. See Qwen3.6 35B-A3B on Nvidia GeForce RTX 5090 (32GB).

Q4_K_M needed
~24.5 GB
Usable on device
~12 GB
Device memory
16 GB
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Which quant fits

Quant ladder vs ~12 GB usable
Q2_K
~17.3 GB
Q3_K_M
~19.8 GB
Q4_K_M
~24.5 GB
Q5_K_M
~27.9 GB
Q6_K
~31.7 GB
Q8_0
~39.1 GB
FP16
~71.6 GB
The line marks Samsung Galaxy S26 Ultra (16GB, 1TB config)'s ~12 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 Qwen3.6
Parameters
36B (MoE, 3B active)
Q4_K_M size
22.29 GB
Q8_0 size
36.9 GB
Context
256k
Ollama tag
qwen3.6:35b-a3b
Full Qwen3.6 35B-A3B requirements →
Device Android
Memory
16 GB ram
Usable for weights
~12 GB
Best runtime
llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)
Best models for Samsung Galaxy S26 Ultra (16GB, 1TB config) →

What you can run instead

Run Qwen3.6 35B-A3B on other hardware

FAQ

Can Samsung Galaxy S26 Ultra (16GB, 1TB config) run Qwen3.6 35B-A3B?

No. Qwen3.6 35B-A3B needs ~24.5 GB even at Q4_K_M, but Samsung Galaxy S26 Ultra (16GB, 1TB config) only has ~12 GB usable.

How much memory does Qwen3.6 35B-A3B need?

Samsung Galaxy S26 Ultra (16GB, 1TB config) does not have enough memory. At Q4_K_M the weights are ~22.29 GB; with KV cache and runtime overhead, budget ~24.5 GB at a 4k context. It is a Mixture-of-Experts model (36B total / 3B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Qwen3.6 35B-A3B 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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Qwen3.6 35B-A3B on Samsung Galaxy S26 Ultra (16GB, 1TB config) compatibility badge A live badge for your model card or README, updated as the data is.
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$ [![Qwen3.6 35B-A3B on Samsung Galaxy S26 Ultra (16GB, 1TB config)](https://localmodel.run/badge/qwen3.6-35b-a3b/samsung-s26-ultra.svg)](https://localmodel.run/can-i-run/qwen3.6-35b-a3b/samsung-s26-ultra)

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.