text model · Qwen2.5-VL · Windows
Can I run Qwen2.5-VL 3B on Nvidia GeForce RTX 4090 (24GB)?
Yes. Qwen2.5-VL 3B runs on Nvidia GeForce RTX 4090 (24GB) at Q4_K_M (~4.4 GB of ~23 GB usable).
Runs at Q4_K_M using ~4.4 GB of ~23 GB usable. You have room for FP16 for higher quality.
- Q4_K_M needed
- ~4.4 GB
- Usable on device
- ~23 GB
- Device memory
- 24 GB
- Best quant
- Q4_K_M
Run it
Pick your tool. All three load the same Q4_K_M weights.
llama-cli -hf ggml-org/Qwen2.5-VL-3B-Instruct-GGUF:Q4_K_M lms get ggml-org/Qwen2.5-VL-3B-Instruct-GGUF AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
How to run it
On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.). AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
- Parameters
- 3.75B
- Q4_K_M size
- 3.05 GB
- Q8_0 size
- 5.1 GB
- Context
- 32k
- Memory
- 24 GB vram
- Usable for weights
- ~23 GB
- Best runtime
- vLLM (Linux) / Ollama (CUDA)
You could also run
Run Qwen2.5-VL 3B on other hardware
FAQ
Can Nvidia GeForce RTX 4090 (24GB) run Qwen2.5-VL 3B?
Yes. Qwen2.5-VL 3B runs on Nvidia GeForce RTX 4090 (24GB) at Q4_K_M (~4.4 GB of ~23 GB usable).
How much memory does Qwen2.5-VL 3B need?
Nvidia GeForce RTX 4090 (24GB) has room to spare. At Q4_K_M the weights are ~3.05 GB; with KV cache and runtime overhead, budget ~4.4 GB at a 4k context.
What is the best tool to run Qwen2.5-VL 3B 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.
Sources
Memory figures are estimates. See methodology.