Yes — Gemma 4.5 12B (12B) runs at 75 tok/s on M5 Max with 128 GB RAM using Q4_K_M quantization via MLX. First token latency is 0.4s. 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 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 | 75 tok/s |
| Time to first token | 0.4s |
| Quantization | Q4_K_M |
| Minimum RAM | 128 GB |
| Recommended engine | MLX |
| Parameters | 12B |
| Benchmark date | 2026-06 |
Q4_K_M 12B MLX M5 Max
The recommended engine for Gemma 4.5 12B on M5 Max is MLX. Install with pip and pull the model:
Alternatively, you can use Ollama for a simpler setup:
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| 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 |
| M2 | 35 tok/s | 1.0s | 16 GB | Ollama |
To run Gemma 4.5 12B on M5 Max you need:
Gemma 4.5 12B needs about 128 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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