Yes — Gemma 4.5 12B (12B) runs at 35 tok/s on M2 with 16 GB RAM using Q4_K_M quantization via Ollama. First token latency is 1.0s. A capable open-source LLM with 12B parameters.
Want to run Gemma 4.5 12B faster — or step up to bigger models? Find your Mac →The LLMCheck index estimates Gemma 4.5 12B on M2 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 | 35 tok/s |
| Time to first token | 1.0s |
| Quantization | Q4_K_M |
| Minimum RAM | 16 GB |
| Recommended engine | Ollama |
| Parameters | 12B |
| Benchmark date | 2026-06 |
Q4_K_M 12B Ollama M2
The recommended engine for Gemma 4.5 12B on M2 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 | 75 tok/s | 0.4s | 128 GB | MLX |
| M4 Pro | 58 tok/s | 0.5s | 24 GB | MLX |
| M5 Pro | 52 tok/s | 0.6s | 24 GB | Ollama |
| M3 | 42 tok/s | 0.8s | 16 GB | Ollama |
To run Gemma 4.5 12B on M2 you need:
Gemma 4.5 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 4.5 12B stacks up against other models on your specific Mac hardware.
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