text model · Gemma · macOS
Can I run Gemma 2 27B on Apple M4 Max (64GB)?
Yes. Gemma 2 27B runs on Apple M4 Max (64GB) at Q4_K_M (~18.7 GB of ~48 GB usable).
Runs at Q4_K_M using ~18.7 GB of ~48 GB usable. You have room for Q8_0 for higher quality.
That figure is at a 4k context and moves about ±15% as context length changes. Apple M4 Max (64GB) leaves ~29.3 GB of headroom, room to step up to Q8_0 for higher quality.
- Q4_K_M needed
- ~18.7 GB
- Usable on device
- ~48 GB
- Device memory
- 64 GB
- Best quant
- Q4_K_M
Which quant fits
Running cost · estimate
- Power draw
- ~145 W
- Electricity / 1M tokens
- ~$0.23
- Pays for itself after
- ~12,959M tok
At ~$0.15/kWh and the estimated ~26 tok/s, a million generated tokens costs about $0.23 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$3,499 Apple M4 Max (64GB) pays for itself after roughly 12,959 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.
Run it
Pick your tool. All 3 load the same Q4_K_M weights.
ollama run gemma2:27b llama-cli -hf bartowski/gemma-2-27b-it-GGUF:Q4_K_M lms get bartowski/gemma-2-27b-it-GGUF - Parameters
- 27B
- Q4_K_M size
- 16.65 GB
- Q8_0 size
- 28.94 GB
- Context
- 8k
- Ollama tag
- gemma2:27b
- Memory
- 64 GB unified
- Usable for weights
- ~48 GB
- Power draw
- ~145 W
- Best runtime
- MLX direct / Ollama (MLX backend)
You could also run
Run Gemma 2 27B on other hardware
FAQ
Can Apple M4 Max (64GB) run Gemma 2 27B?
Yes. Gemma 2 27B runs on Apple M4 Max (64GB) at Q4_K_M (~18.7 GB of ~48 GB usable).
How much memory does Gemma 2 27B need?
Apple M4 Max (64GB) has room to spare. At Q4_K_M the weights are ~16.65 GB; with KV cache and runtime overhead, budget ~18.7 GB at a 4k context.
What is the best tool to run Gemma 2 27B 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.
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A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/gemma-2-27b/apple-m4-max-64gb) Sources
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.