Yes — Gemma 4.5 27B (27B) runs at 32 tok/s on M3 Max with 64 GB RAM using Q4_K_M quantization via Ollama. First token latency is 0.9s. A capable open-source LLM with 27B parameters.
LLMCheck measured Gemma 4.5 27B on M3 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 | 32 tok/s |
| Time to first token | 0.9s |
| Quantization | Q4_K_M |
| Minimum RAM | 64 GB |
| Recommended engine | Ollama |
| Parameters | 27B |
| Benchmark date | 2026-07 |
Q4_K_M 27B Ollama M3 Max
The recommended engine for Gemma 4.5 27B on M3 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 |
|---|---|---|---|---|
| M5 Max | 42 tok/s | 0.6s | 128 GB | MLX |
| M4 Max | 36 tok/s | 0.7s | 48 GB | MLX |
| M5 Pro | 30 tok/s | 0.9s | 32 GB | Ollama |
| M4 Pro | 26 tok/s | 1.0s | 32 GB | Ollama |
To run Gemma 4.5 27B on M3 Max you need:
Gemma 4.5 27B needs about 64 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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