Gemma 2 9B needs ~17.0 GB VRAM. MacBook Pro M4 Max 48GB has 34.6 GB. With Q4_K_M quantization, expect ~72 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
71.7 tok/s
TTFT
2700 ms
Safe context
8K
Memory
17.0 GB / 34.6 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 | 71.7 tok/s | 1473 ms | 8K |
| Coding | B | Runs well | 71.7 tok/s | 2700 ms | 8K |
| Agentic Coding | B | Runs well | 71.7 tok/s | 3927 ms | 8K |
| Reasoning | B | Runs well | 71.7 tok/s | 3191 ms | 8K |
| RAG | B | Runs well | 71.7 tok/s | 4909 ms | 8K |
How Gemma 2 9B (9B params) fits at each quantization level on MacBook Pro M4 Max 48GB (34.6 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B57 |
Q3_K_S | 3 | 4.4 GB | Low | B58 |
NVFP4 | 4 | 5.0 GB | Medium | B58 |
Q4_K_M | 4 | 5.5 GB | Medium | B58 |
Q5_K_M | 5 | 6.5 GB | High | B58 |
Q6_K | 6 | 7.4 GB | High | B59 |
Q8_0 | 8 | 9.6 GB | Very High | B59 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | B64 |
Copy-paste commands to run Gemma 2 9B on your machine.
Run
ollama run gemma2Yes, MacBook Pro M4 Max 48GB can run Gemma 2 9B with a B grade (Runs well). Expected decode speed: 71.7 tok/s.
Gemma 2 9B (9B parameters) requires approximately 17.0 GB of memory with Q4_K_M quantization.
The recommended quantization for Gemma 2 9B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Max 48GB, Gemma 2 9B achieves approximately 71.7 tokens per second decode speed with a time-to-first-token of 2700ms using Q4_K_M quantization.
For coding workloads, Gemma 2 9B on MacBook Pro M4 Max 48GB receives a B grade with 71.7 tok/s and 8K context.
On MacBook Pro M4 Max 48GB, Gemma 2 9B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Not always. MacBook Pro M4 Max 48GB 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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/gemma-2-9b-on-m4-max-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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