Yes — Gemma 3 12B (12B) runs at 68 tok/s on M5 Max with 64 GB RAM using Q4_K_M quantization via Ollama. First token latency is 0.6s. Google's 12B model offering strong reasoning for mid-range Macs.
Want to run Gemma 3 12B faster — or step up to bigger models? Find your Mac →The LLMCheck index estimates Gemma 3 12B on M5 Max using our published methodology: Q4_K_M quantization, memory-bandwidth scaling, and cross-referenced third-party benchmarks where available. Figures are transparent estimates — own this config? Submit a real benchmark →
| Metric | Value |
|---|---|
| Tokens per second | 68 tok/s |
| Time to first token | 0.6s |
| Quantization | Q4_K_M |
| Minimum RAM | 64 GB |
| Recommended engine | Ollama |
| Parameters | 12B |
| Benchmark date | 2026-03 |
Q4_K_M 12B Ollama M5 Max
The recommended engine for Gemma 3 12B on M5 Max is Ollama. Install Ollama, then pull the model:
Ollama handles quantization automatically — it will download the Q4_K_M variant (~64 GB) and start an interactive chat session.
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| M4 Pro | 52 tok/s | 0.7s | 24 GB | MLX |
| M3 | 38 tok/s | 1.1s | 16 GB | Ollama |
| M2 | 32 tok/s | 1.3s | 16 GB | Ollama |
To run Gemma 3 12B on M5 Max you need:
Gemma 3 12B needs about 64 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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See how Gemma 3 12B stacks up against other models on your specific Mac hardware.
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