Can NVIDIA A100 40GB run Qwen 2.5 72B?
72B parameter LLM model on 40GB HBM2e
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 A100 40GB only has 40GB — not enough even at maximum compression.
FP16 (Full Precision)144GB (need 104GB more)
Maximum quality, no quantization
Q8 (8-bit)72GB (need 32GB more)
Near-lossless, ~50% size reduction
Q4 (4-bit)42GB (need 2GB more)
Good quality, ~75% size reduction
Your GPU VRAM: 40GB HBM2e at 1555 GB/s bandwidth
Recommended system RAM: 80GB DDR5 (2x GPU VRAM minimum for model overflow)
Recommended system RAM: 80GB 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 A100 40GB Specs
VRAM40GB HBM2e
Memory Bandwidth1555 GB/s
TDP250W
CUDA Cores6,912
Street Price~$4500
AI Rating10/10
Other GPUs That Run Qwen 2.5 72B
Other LLM Models on NVIDIA A100 40GB
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)