# Can I run Qwen2.5 72B on Nvidia GeForce RTX 4090 (24GB)?

> **No, not enough memory.** Needs ~50.2 GB even at Q4_K_M, but only ~23 GB is usable.

Last validated: 2026-06-15.

## Memory math
- Qwen2.5 72B: 72B; Q4_K_M weighs 47.42 GB on disk.
- At Q4_K_M with a 4k context it needs ~50.2 GB (weights + KV cache + ~0.8 GB runtime overhead, ±15% with context length).
- Nvidia GeForce RTX 4090 (24GB): 24 GB vram, ~23 GB usable for model weights.
- Headroom: ~-27.2 GB.

## How to run
Recommended quant: n/a. Best tool on Windows: LM Studio.

```sh
ollama run qwen2.5:72b
```

## Run Qwen2.5 72B on other devices
- [Apple M4 Max (128GB)](https://localmodel.run/can-i-run/qwen2.5-72b/apple-m4-max-128gb)
- [Apple M5 Max (128GB)](https://localmodel.run/can-i-run/qwen2.5-72b/apple-m5-max-128gb)
- [Apple M3 Ultra (256GB)](https://localmodel.run/can-i-run/qwen2.5-72b/apple-m3-ultra-256gb)

## Other models that run on Nvidia GeForce RTX 4090 (24GB)
- [Command R 35B (35B)](https://localmodel.run/can-i-run/command-r-35b/nvidia-rtx-4090-24gb)
- [Yi 1.5 34B (34B)](https://localmodel.run/can-i-run/yi-1.5-34b/nvidia-rtx-4090-24gb)
- [Qwen2.5 32B (32B)](https://localmodel.run/can-i-run/qwen2.5-32b/nvidia-rtx-4090-24gb)
- [Qwen3 32B (32B)](https://localmodel.run/can-i-run/qwen3-32b/nvidia-rtx-4090-24gb)
- [DeepSeek-R1-Distill-Qwen 32B (32B)](https://localmodel.run/can-i-run/deepseek-r1-distill-qwen-32b/nvidia-rtx-4090-24gb)
- [Qwen2.5 Coder 32B (32B)](https://localmodel.run/can-i-run/qwen2.5-coder-32b/nvidia-rtx-4090-24gb)

Estimate, not a guarantee. Sources: https://ollama.com/library/qwen2.5, https://huggingface.co/bartowski/Qwen2.5-72B-Instruct-GGUF, https://qwenlm.github.io/blog/qwen2.5/, https://lmarena.ai/leaderboard.
More: https://localmodel.run/can-i-run/qwen2.5-72b/nvidia-rtx-4090-24gb