text model · Yi · Windows
Yi Can I run Yi 1.5 34B on Nvidia GeForce RTX 3090 (24GB)?
Yes. Yi 1.5 34B runs on Nvidia GeForce RTX 3090 (24GB) at Q4_K_M (~21.4 GB of ~23 GB usable).
Fits at Q4_K_M (~21.4 GB of ~23 GB usable) but with little headroom, close other apps.
- Q4_K_M needed
- ~21.4 GB
- Usable on device
- ~23 GB
- Device memory
- 24 GB
- Best quant
- Q4_K_M
Run it
Pick your tool. All three load the same Q4_K_M weights.
llama-cli -hf bartowski/Yi-1.5-34B-Chat-GGUF:Q4_K_M lms get bartowski/Yi-1.5-34B-Chat-GGUF AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
How to run it
On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.). AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
- Parameters
- 34B
- Q4_K_M size
- 19.24 GB
- Q8_0 size
- 34.03 GB
- Context
- 32k
- Memory
- 24 GB vram
- Usable for weights
- ~23 GB
- Best runtime
- vLLM (Linux) / Ollama (CUDA)
You could also run
Run Yi 1.5 34B on other hardware
FAQ
Can Nvidia GeForce RTX 3090 (24GB) run Yi 1.5 34B?
Yes. Yi 1.5 34B runs on Nvidia GeForce RTX 3090 (24GB) at Q4_K_M (~21.4 GB of ~23 GB usable).
How much memory does Yi 1.5 34B need?
It is a tight fit on Nvidia GeForce RTX 3090 (24GB). At Q4_K_M the weights are ~19.24 GB; with KV cache and runtime overhead, budget ~21.4 GB at a 4k context.
What is the best tool to run Yi 1.5 34B 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.