text model · Hunyuan · Windows

Can I run Hunyuan-A13B-Instruct on Nvidia GeForce RTX 4080 (16GB)?

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 Nvidia GeForce RTX 4080 (16GB) only has ~15 GB usable.

Needs ~48.3 GB Device usable ~15 GB

Needs ~48.3 GB even at Q4_K_M, but only ~15 GB is usable.

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

The gap is about 33.3 GB: Hunyuan-A13B-Instruct needs roughly 48.3 GB at Q4_K_M and Nvidia GeForce RTX 4080 (16GB) leaves only about 15 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: ~15 GB
Device memory: 16 GB

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Which quant fits

Quant ladder vs ~15 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 Nvidia GeForce RTX 4080 (16GB)'s ~15 GB budget; rungs past it are too large.

How to run it

On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.).

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 Windows

Memory: 16 GB vram
Usable for weights: ~15 GB
Power draw: ~320 W
Best runtime: vLLM (Linux) / Ollama (CUDA)

Best models for Nvidia GeForce RTX 4080 (16GB) →

What you can run instead

Run Hunyuan-A13B-Instruct on other hardware

Apple M4 Max (128GB)AMD Ryzen AI Halo (128GB)Apple M5 Max (128GB)Apple M3 Ultra (256GB)

FAQ

Can Nvidia GeForce RTX 4080 (16GB) run Hunyuan-A13B-Instruct?

No. Hunyuan-A13B-Instruct needs ~48.3 GB even at Q4_K_M, but Nvidia GeForce RTX 4080 (16GB) only has ~15 GB usable.

How much memory does Hunyuan-A13B-Instruct need?

Nvidia GeForce RTX 4080 (16GB) 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 Windows?

LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.

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[![Hunyuan-A13B-Instruct on Nvidia GeForce RTX 4080 (16GB)](https://localmodel.run/badge/hunyuan-a13b/nvidia-rtx-4080-16gb.svg)](https://localmodel.run/can-i-run/hunyuan-a13b/nvidia-rtx-4080-16gb)

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.