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text model · Hunyuan · Android

Can I run Hunyuan-A13B-Instruct on Samsung Galaxy S24 Ultra?

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

No. Hunyuan-A13B-Instruct needs ~48.3 GB even at Q4_K_M, but Samsung Galaxy S24 Ultra only has ~8.5 GB usable.

Needs ~48.3 GB Device usable ~8.5 GB

Needs ~48.3 GB even at Q4_K_M, but only ~8.5 GB is usable.

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

The gap is about 39.8 GB: Hunyuan-A13B-Instruct needs roughly 48.3 GB at Q4_K_M and Samsung Galaxy S24 Ultra leaves only about 8.5 GB usable for a model. The lightest tracked hardware that runs Hunyuan-A13B-Instruct is the Apple M4 Max (128GB) at 128 GB. See Hunyuan-A13B-Instruct on Apple M4 Max (128GB).

Q4_K_M needed
~48.3 GB
Usable on device
~8.5 GB
Device memory
12 GB
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Which quant fits

Quant ladder vs ~8.5 GB usable
Q2_K
~36.4 GB
Q3_K_M
~42 GB
Q4_K_M
~48.3 GB
Q5_K_M
~59.9 GB
Q6_K
~68.5 GB
Q8_0
~82.5 GB
FP16
~163.9 GB
The line marks Samsung Galaxy S24 Ultra's ~8.5 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 Hunyuan
Parameters
80B (MoE, 13B active)
Q4_K_M size
45.43 GB
Q8_0 size
79.58 GB
Context
256k
Full Hunyuan-A13B-Instruct requirements →
Device Android
Memory
12 GB ram
Usable for weights
~8.5 GB
Power draw
~8 W
Best runtime
llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)
Best models for Samsung Galaxy S24 Ultra →

What you can run instead

Run Hunyuan-A13B-Instruct on other hardware

FAQ

Can Samsung Galaxy S24 Ultra run Hunyuan-A13B-Instruct?

No. Hunyuan-A13B-Instruct needs ~48.3 GB even at Q4_K_M, but Samsung Galaxy S24 Ultra only has ~8.5 GB usable.

How much memory does Hunyuan-A13B-Instruct need?

Samsung Galaxy S24 Ultra does not have enough memory. At Q4_K_M the weights are ~45.43 GB; with KV cache and runtime overhead, budget ~48.3 GB at a 4k context. It is a Mixture-of-Experts model (80B total / 13B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Hunyuan-A13B-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.