Yes — Gemma 3 4B (4B) runs at 48 tok/s on M1 with 8 GB RAM using Q4_K_M quantization via Ollama. First token latency is 0.8s. Google's previous-gen 4B dense model, solid balance of speed and quality.
LLMCheck measured Gemma 3 4B on M1 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 | 48 tok/s |
| Time to first token | 0.8s |
| Quantization | Q4_K_M |
| Minimum RAM | 8 GB |
| Recommended engine | Ollama |
| Parameters | 4B |
| Benchmark date | 2025-12 |
Q4_K_M 4B Ollama M1
The recommended engine for Gemma 3 4B on M1 is Ollama. Install Ollama, then pull the model:
Ollama handles quantization automatically — it will download the Q4_K_M variant (~8 GB) and start an interactive chat session.
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| M5 Max | 132 tok/s | 0.3s | 64 GB | Ollama |
| M3 Pro | 88 tok/s | 0.4s | 18 GB | MLX |
To run Gemma 3 4B on M1 you need:
See how Gemma 3 4B stacks up against other models on your specific Mac hardware.
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