Gemma 3 4B needs ~12.3 GB VRAM. MacBook Pro M3 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~56 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
56.0 tok/s
TTFT
3457 ms
Safe context
128K
Memory
12.3 GB / 46.1 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 | 56.0 tok/s | 1886 ms | 128K |
| Coding | B | Runs well | 56.0 tok/s | 3457 ms | 128K |
| Agentic Coding | B | Runs well | 56.0 tok/s | 5029 ms | 128K |
| Reasoning | B | Runs well | 56.0 tok/s | 4086 ms | 128K |
| RAG | B | Runs well | 56.0 tok/s | 6286 ms | 128K |
How Gemma 3 4B (4B params) fits at each quantization level on MacBook Pro M3 Max 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.6 GB | Low | B63 |
Q3_K_S | 3 | 2.0 GB | Low | B63 |
NVFP4 | 4 |
Copy-paste commands to run Gemma 3 4B on your machine.
Run
ollama run gemma3:4bYes, MacBook Pro M3 Max 64GB can run Gemma 3 4B with a B grade (Runs well). Expected decode speed: 56.0 tok/s.
Gemma 3 4B (4B parameters) requires approximately 12.3 GB of memory with Q4_K_M quantization.
The recommended quantization for Gemma 3 4B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M3 Max 64GB, Gemma 3 4B achieves approximately 56.0 tokens per second decode speed with a time-to-first-token of 3457ms using Q4_K_M quantization.
For coding workloads, Gemma 3 4B on MacBook Pro M3 Max 64GB receives a B grade with 56.0 tok/s and 128K context.
On MacBook Pro M3 Max 64GB, Gemma 3 4B can safely use up to 128K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/gemma-3-4b-on-m3-max-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
2.2 GB |
| Medium |
| B63 |
Q4_K_M | 4 | 2.4 GB | Medium | B63 |
Q5_K_M | 5 | 2.9 GB | High | B63 |
Q6_K | 6 | 3.3 GB | High | B63 |
Q8_0 | 8 | 4.3 GB | Very High | B63 |
F16Best for your GPU | 16 | 8.2 GB | Maximum | B64 |
Not always. MacBook Pro M3 Max 64GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.