text model · Yi · macOS
Can I run Yi 1.5 34B on Apple M4 Pro (48GB)?
Yes. Yi 1.5 34B runs on Apple M4 Pro (48GB) at Q4_K_M (~21.4 GB of ~32 GB usable).
Runs at Q4_K_M using ~21.4 GB of ~32 GB usable.
That figure is at a 4k context and moves about ±15% as context length changes. Apple M4 Pro (48GB) leaves ~10.6 GB of headroom.
- Q4_K_M needed
- ~21.4 GB
- Usable on device
- ~32 GB
- Device memory
- 48 GB
- Best quant
- Q4_K_M
Which quant fits
Running cost · estimate
- Power draw
- ~140 W
- Electricity / 1M tokens
- ~$0.53
At ~$0.15/kWh and the estimated ~11 tok/s, a million generated tokens costs about $0.53 in electricity. TDP is the peak draw, so this is an upper bound. Assumptions.
Run it
Pick your tool. All 2 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 How to run it
On macOS use LM Studio (Polished GUI, ships MLX on Apple Silicon, one-click model downloads.).
- Parameters
- 34B
- Q4_K_M size
- 19.24 GB
- Q8_0 size
- 34.03 GB
- Context
- 32k
- Memory
- 48 GB unified
- Usable for weights
- ~32 GB
- Power draw
- ~140 W
- Best runtime
- Ollama (MLX backend) / MLX direct
You could also run
Run Yi 1.5 34B on other hardware
FAQ
Can Apple M4 Pro (48GB) run Yi 1.5 34B?
Yes. Yi 1.5 34B runs on Apple M4 Pro (48GB) at Q4_K_M (~21.4 GB of ~32 GB usable).
How much memory does Yi 1.5 34B need?
Apple M4 Pro (48GB) has room to spare. 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 macOS?
LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.
Embed this
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/yi-1.5-34b/apple-m4-pro-48gb) Sources
- apple.com/newsroom/2024/10/apple-introduces-m4-pro-and-m4-max
- apple.com/newsroom/2024/10/new-macbook-pro-features-m4-family-of-chips-and-apple-intelligence
- blog.peddals.com
- github.com/ml-explore
- github.com/raullenchai
- huggingface.co/01-ai
- huggingface.co/bartowski
- lmstudio.ai
- support.apple.com/en-us/103253
- support.apple.com/en-us/121553
- support.apple.com/en-us/121555
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.