Can I run it?
Can I run gemma 4 12b it on Apple M1 Max?
Tight fit
Tight fit fully in unified memory on your Apple M1 Max at BF16, 4K context, about 8.6–12 tok/s. Weights 22.2 GB plus 0.56 GB of KV cache — 23.3 GB of 24.0 GB usable.
Best quantBF16
Working context4K
Max that fits4K
Speed8.6–12 tok/sEstimate from memory bandwidth, not a benchmark. Method.
Weights22.2 GB
KV cache0.56 GB
Total23.3 GB
Usable24.0 GB
gemma 4 12b it details · Apple M1 Max page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/gemma-4-12b-it-GGUF:BF16 -c 4096 -ngl 48
Ollama
ollama run gemma
LM Studio
lms get unsloth/gemma-4-12b-it-GGUF # Then load quant BF16
Assumptions
- Estimate from memory bandwidth, not a benchmark. Decode speed uses 55–75% of peak bandwidth.
- KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
- BF16 size is the real GGUF file size from Hugging Face.
- Unified memory uses 75% for the GPU by default, and always leaves about 5 GB for the OS.
- Speed is quoted at 4K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Qwen3.8 27B on Apple M1 Max? — Tight fit, UD-Q6_K_L, 9.0–12 tok/s (estimate)
- Can I run Qwen3.6 35B A3B on Apple M1 Max? — Tight fit, UD-Q4_K_XL, 24–32 tok/s (estimate)
- Can I run Qwen3.8 35B A3B Distill on Apple M1 Max? — Tight fit, Q4_K_M, 24–33 tok/s (estimate)
Updated 2026-10-24. Profile on this page is the device default.