Raises estimated decode speed by about 38%.
~$1,999 MSRP
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VOOZH | about |
Gemma 3 4B needs ~8.9 GB VRAM. Mac mini M4 32GB has 23.0 GB. With Q4_K_M quantization, expect ~27 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
25.9 tok/s
TTFT
7468 ms
Safe context
125K
Memory
8.9 GB / 23.0 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 26.8 tok/s | 3935 ms | 125K |
| Coding | B | Runs well | 26.8 tok/s | 7214 ms | 125K |
| Agentic Coding | B | Runs well | 26.8 tok/s | 10494 ms | 125K |
| Reasoning | B | Runs well | 26.8 tok/s | 8526 ms | 125K |
| RAG | B | Runs well | 26.8 tok/s | 13117 ms | 125K |
How Gemma 3 4B (4B params) fits at each quantization level on Mac mini M4 32GB (23.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.6 GB | Low | B65 |
Q3_K_S | 3 | 2.0 GB | Low | B65 |
NVFP4 | 4 |
Copy-paste commands to run Gemma 3 4B on your machine.
Run
ollama run gemma3:4bUpgrade options
Raises estimated decode speed by about 38%.
~$1,999 MSRP
Raises estimated decode speed by about 116%.
~$2,499 MSRP
Raises estimated decode speed by about 116%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
2.2 GB |
| Medium |
| B66 |
Q4_K_M | 4 | 2.4 GB | Medium | B66 |
Q5_K_M | 5 | 2.9 GB | High | B66 |
Q6_K | 6 | 3.3 GB | High | B66 |
Q8_0 | 8 | 4.3 GB | Very High | B67 |
F16Best for your GPU | 16 | 8.2 GB | Maximum | B69 |