Can NVIDIA GeForce RTX 5090 run Qwen 2.5 72B?
72B parameter LLM model on 32GB GDDR7
Barely — requires CPU/RAM offloading
~1-3 tok/s (offload)
SpeedVery slow — expect 1-3 tokens/sec
QualityQuality is fine but the speed makes it impractical for interactive use
VRAM Requirements
Qwen 2.5 72B is a 72B parameter model. At full precision (FP16), it requires 144GB of VRAM. Your NVIDIA GeForce RTX 5090 only has 32GB — not enough even at maximum compression.
FP16 (Full Precision)144GB (need 112GB more)
Maximum quality, no quantization
Q8 (8-bit)72GB (need 40GB more)
Near-lossless, ~50% size reduction
Q4 (4-bit)42GB (need 10GB more)
Good quality, ~75% size reduction
Your GPU VRAM: 32GB GDDR7 at 1792 GB/s bandwidth
Recommended system RAM: 64GB DDR5 (2x GPU VRAM minimum for model overflow)
Recommended system RAM: 64GB DDR5 (2x GPU VRAM minimum for model overflow)
How to Set It Up
Step 1: Install Ollama
curl -fsSL https://ollama.com/install.sh | shOllama is the easiest way to run local LLMs. Works on Linux, macOS, and Windows.
Step 2: Download and run Qwen 2.5 72B
ollama run qwen2.5:72b:q4_K_MThis downloads the model (~72GB). First run takes a few minutes.
Step 3: Verify GPU is being used
nvidia-smiCheck that VRAM usage increases when the model loads. You should see ~42GB used.
NVIDIA GeForce RTX 5090 Specs
VRAM32GB GDDR7
Memory Bandwidth1792 GB/s
TDP575W
CUDA Cores21,760
Street Price~$2800
AI Rating10/10
Other GPUs That Run Qwen 2.5 72B
Other LLM Models on NVIDIA GeForce RTX 5090
About Qwen 2.5 72B
Top open LLM for reasoning. Similar requirements to Llama 70B.
Category: LLM · Parameters: 72B · CUDA required: No (runs via llama.cpp/GGUF)