Yes — Gemma 3 27B (27B) runs at 42 tok/s on M5 Max with 64 GB RAM using Q4_K_M quantization via Ollama. First token latency is 0.9s. Google's 27B dense model, best-in-class reasoning for 24–48 GB Macs.
LLMCheck measured Gemma 3 27B on M5 Max using the standard methodology: Q4_K_M quantization, 256-token input, 512-token output, 3 runs averaged on a freshly-booted system.
| Metric | Value |
|---|---|
| Tokens per second | 42 tok/s |
| Time to first token | 0.9s |
| Quantization | Q4_K_M |
| Minimum RAM | 64 GB |
| Recommended engine | Ollama |
| Parameters | 27B |
| Benchmark date | 2026-03 |
Q4_K_M 27B Ollama M5 Max
The recommended engine for Gemma 3 27B 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 Max | 35 tok/s | 1.1s | 48 GB | MLX |
| M3 Max | 28 tok/s | 1.3s | 96 GB | MLX |
| M4 Pro | 25 tok/s | 1.5s | 24 GB | LM Studio |
To run Gemma 3 27B on M5 Max you need:
See how Gemma 3 27B stacks up against other models on your specific Mac hardware.
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