text model · mistral · Windows
Can I run Mixtral 8x7B on Nvidia GeForce RTX 4070 (12GB)?
No. Mixtral 8x7B needs ~28.9 GB even at Q4_K_M, but Nvidia GeForce RTX 4070 (12GB) only has ~11 GB usable.
Needs ~28.9 GB even at Q4_K_M, but only ~11 GB is usable.
- Q4_K_M needed
- ~28.9 GB
- Usable on device
- ~11 GB
- Device memory
- 12 GB
- Parameters
- 46.7B (MoE, 12.9B active)
- Q4_K_M size
- 26.49 GB
- Q8_0 size
- 46.22 GB
- Context
- 32k
- Ollama tag
- mixtral:8x7b
- Memory
- 12 GB vram
- Usable for weights
- ~11 GB
- Best runtime
- Ollama (CUDA) / vLLM (Linux)
What you can run instead
Run Mixtral 8x7B on other hardware
FAQ
Can Nvidia GeForce RTX 4070 (12GB) run Mixtral 8x7B?
No. Mixtral 8x7B needs ~28.9 GB even at Q4_K_M, but Nvidia GeForce RTX 4070 (12GB) only has ~11 GB usable.
How much memory does Mixtral 8x7B need?
Nvidia GeForce RTX 4070 (12GB) does not have enough memory. At Q4_K_M the weights are ~26.49 GB; with KV cache and runtime overhead, budget ~28.9 GB at a 4k context. It is a Mixture-of-Experts model (46.7B total / 12.9B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Mixtral 8x7B 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.