Yes — Gemma 3 12B (12B) runs at 11 tok/s on M3 with 16 GB RAM using Q4_K_M quantization via Ollama. 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 M3 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 | 11 tok/s |
| Time to first token | — |
| Quantization | Q4_K_M |
| Minimum RAM | 16 GB |
| Recommended engine | Ollama |
| Parameters | 12B |
| Benchmark date | 2026-01 |
Q4_K_M 12B Ollama M3
The recommended engine for Gemma 3 12B on M3 is Ollama. Install Ollama, then pull the model:
Ollama handles quantization automatically — it will download the Q4_K_M variant (~16 GB) and start an interactive chat session.
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| M5 Max | 64 tok/s | — | 64 GB | Ollama |
| M2 | 11 tok/s | — | 16 GB | Ollama |
To run Gemma 3 12B on M3 you need:
Gemma 3 12B needs about 16 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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