Can I run it?
Can I run gemma 4 E4B it on Apple M5?
Runs
Runs fully in unified memory on your Apple M5 at UD-Q8_K_XL, 8K context, about 8.9–12 tok/s. Weights 8.11 GB plus 0.14 GB of KV cache — 8.64 GB of 11.0 GB usable. Up to 128K context still fits.
Best quantUD-Q8_K_XL
Working context8K
Max that fits128K
Speed8.9–12 tok/s
Weights8.11 GB
KV cache0.14 GB
Total8.64 GB
Usable11.0 GB
gemma 4 E4B it details · Apple M5 page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/gemma-4-E4B-it-GGUF:UD-Q8_K_XL -c 8192 -ngl 42
Ollama
ollama run gemma
LM Studio
lms get unsloth/gemma-4-E4B-it-GGUF # Then load quant UD-Q8_K_XL
Assumptions
- Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
- 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%.
- UD-Q8_K_XL 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 8K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Qwen3.8 27B on Apple M5? — Tight fit, UD-Q2_K_XL, 8.1–11 tok/s
- Can I run gemma 4 12b it on Apple M5? — Tight fit, Q6_K, 6.5–8.8 tok/s
- Can I run Qwen3.5 9B on Apple M5? — Tight fit, Q8_0, 8.6–12 tok/s
Updated 2026-10-24. Profile on this page is the device default.