text model · mistral · Windows
Can I run Mistral 7B on Nvidia GeForce RTX 4080 (16GB)?
Yes. Mistral 7B runs on Nvidia GeForce RTX 4080 (16GB) at Q4_K_M (~5.8 GB of ~15 GB usable).
Runs at Q4_K_M using ~5.8 GB of ~15 GB usable. You have room for Q8_0 for higher quality.
- Q4_K_M needed
- ~5.8 GB
- Usable on device
- ~15 GB
- Device memory
- 16 GB
- Best quant
- Q4_K_M
Run it
Pick your tool. All three load the same Q4_K_M weights.
ollama run mistral:7b llama-cli -hf bartowski/Mistral-7B-Instruct-v0.3-GGUF:Q4_K_M lms get bartowski/Mistral-7B-Instruct-v0.3-GGUF AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
- Parameters
- 7B
- Q4_K_M size
- 4.37 GB
- Q8_0 size
- 7.7 GB
- Context
- 32k
- Ollama tag
- mistral:7b
- Memory
- 16 GB vram
- Usable for weights
- ~15 GB
- Best runtime
- vLLM (Linux) / Ollama (CUDA)
You could also run
Run Mistral 7B on other hardware
FAQ
Can Nvidia GeForce RTX 4080 (16GB) run Mistral 7B?
Yes. Mistral 7B runs on Nvidia GeForce RTX 4080 (16GB) at Q4_K_M (~5.8 GB of ~15 GB usable).
How much memory does Mistral 7B need?
Nvidia GeForce RTX 4080 (16GB) has room to spare. At Q4_K_M the weights are ~4.37 GB; with KV cache and runtime overhead, budget ~5.8 GB at a 4k context.
What is the best tool to run Mistral 7B 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.