Yes — Gemma 3 4B (4B) runs at 132 tok/s on M5 Max with 64 GB RAM using Q4_K_M quantization via Ollama. First token latency is 0.3s. Google's previous-gen 4B dense model, solid balance of speed and quality.
Want to run Gemma 3 4B faster — or step up to bigger models? Find your Mac →The LLMCheck index estimates Gemma 3 4B 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 | 132 tok/s |
| Time to first token | 0.3s |
| Quantization | Q4_K_M |
| Minimum RAM | 64 GB |
| Recommended engine | Ollama |
| Parameters | 4B |
| Benchmark date | 2026-03 |
Q4_K_M 4B Ollama M5 Max
The recommended engine for Gemma 3 4B 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 |
|---|---|---|---|---|
| M3 Pro | 88 tok/s | 0.4s | 18 GB | MLX |
| M1 | 48 tok/s | 0.8s | 8 GB | Ollama |
To run Gemma 3 4B on M5 Max you need:
Gemma 3 4B needs about 64 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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See how Gemma 3 4B stacks up against other models on your specific Mac hardware.
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