text model · ERNIE · Windows
Can I run ERNIE 4.5 21B-A3B on Nvidia GeForce RTX 5090 (32GB)?
Yes. ERNIE 4.5 21B-A3B runs on Nvidia GeForce RTX 5090 (32GB) at Q4_K_M (~14.3 GB of ~31 GB usable).
Runs at Q4_K_M using ~14.3 GB of ~31 GB usable. You have room for Q8_0 for higher quality.
That figure is at a 4k context and moves about ±15% as context length changes. Nvidia GeForce RTX 5090 (32GB) leaves ~16.7 GB of headroom, room to step up to Q8_0 for higher quality.
- Q4_K_M needed
- ~14.3 GB
- Usable on device
- ~31 GB
- Device memory
- 32 GB
- Best quant
- Q4_K_M
Which quant fits
Run it
Pick your tool. All 2 load the same Q4_K_M weights.
llama-cli -hf unsloth/ERNIE-4.5-21B-A3B-PT-GGUF:Q4_K_M lms get unsloth/ERNIE-4.5-21B-A3B-PT-GGUF How to run it
On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.).
- Parameters
- 21B (MoE, 3B active)
- Q4_K_M size
- 12.42 GB
- Q8_0 size
- 21.61 GB
- Context
- 131k
- Memory
- 32 GB vram
- Usable for weights
- ~31 GB
- Power draw
- ~575 W
- Best runtime
- vLLM (Linux) / Ollama (CUDA)
You could also run
Run ERNIE 4.5 21B-A3B on other hardware
FAQ
Can Nvidia GeForce RTX 5090 (32GB) run ERNIE 4.5 21B-A3B?
Yes. ERNIE 4.5 21B-A3B runs on Nvidia GeForce RTX 5090 (32GB) at Q4_K_M (~14.3 GB of ~31 GB usable).
How much memory does ERNIE 4.5 21B-A3B need?
Nvidia GeForce RTX 5090 (32GB) has room to spare. At Q4_K_M the weights are ~12.42 GB; with KV cache and runtime overhead, budget ~14.3 GB at a 4k context. It is a Mixture-of-Experts model (21B total / 3B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run ERNIE 4.5 21B-A3B 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
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/ernie-4.5-21b-a3b/nvidia-rtx-5090-32gb) 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.