Skip to content

text model · Hunyuan · Windows

Can I run Hunyuan-A13B-Instruct on Nvidia GeForce RTX 3090 (24GB)?

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 3090 (24GB) only has ~23 GB usable.

Needs ~48.3 GB Device usable ~23 GB

Needs ~48.3 GB even at Q4_K_M, but only ~23 GB is usable.

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

The gap is about 25.3 GB: Hunyuan-A13B-Instruct needs roughly 48.3 GB at Q4_K_M and Nvidia GeForce RTX 3090 (24GB) leaves only about 23 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
~23 GB
Device memory
24 GB
Share on X Share on Reddit

Which quant fits

Quant ladder vs ~23 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 3090 (24GB)'s ~23 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
24 GB vram
Usable for weights
~23 GB
Power draw
~350 W
Best runtime
vLLM (Linux) / Ollama (CUDA)
Best models for Nvidia GeForce RTX 3090 (24GB) →

What you can run instead

Run Hunyuan-A13B-Instruct on other hardware

FAQ

Can Nvidia GeForce RTX 3090 (24GB) run Hunyuan-A13B-Instruct?

No. Hunyuan-A13B-Instruct needs ~48.3 GB even at Q4_K_M, but Nvidia GeForce RTX 3090 (24GB) only has ~23 GB usable.

How much memory does Hunyuan-A13B-Instruct need?

Nvidia GeForce RTX 3090 (24GB) 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.

Embed this

Hunyuan-A13B-Instruct on Nvidia GeForce RTX 3090 (24GB) compatibility badge A live badge for your model card or README, updated as the data is.
Markdown
$ [![Hunyuan-A13B-Instruct on Nvidia GeForce RTX 3090 (24GB)](https://localmodel.run/badge/hunyuan-a13b/nvidia-rtx-3090-24gb.svg)](https://localmodel.run/can-i-run/hunyuan-a13b/nvidia-rtx-3090-24gb)

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.