Gemma 2 9B needs ~39.2 GB VRAM. Mac Studio M3 Ultra 256GB has 184.3 GB. With Q4_K_M quantization, expect ~81 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
80.7 tok/s
TTFT
2398 ms
Safe context
8K
Memory
39.2 GB / 184.3 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 | 80.7 tok/s | 1308 ms | 8K |
| Coding | B | Runs well | 80.7 tok/s | 2398 ms | 8K |
| Agentic Coding | B | Runs well | 80.7 tok/s | 3488 ms | 8K |
| Reasoning | B | Runs well | 80.7 tok/s | 2834 ms | 8K |
| RAG | B | Runs well | 80.7 tok/s | 4361 ms | 8K |
How Gemma 2 9B (9B params) fits at each quantization level on Mac Studio M3 Ultra 256GB (184.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C52 |
Q3_K_S | 3 | 4.4 GB | Low | C52 |
NVFP4 | 4 |
Copy-paste commands to run Gemma 2 9B on your machine.
Run
ollama run gemma2Yes, Mac Studio M3 Ultra 256GB can run Gemma 2 9B with a B grade (Runs well). Expected decode speed: 80.7 tok/s.
Gemma 2 9B (9B parameters) requires approximately 39.2 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 Mac Studio M3 Ultra 256GB, Gemma 2 9B achieves approximately 80.7 tokens per second decode speed with a time-to-first-token of 2398ms using Q4_K_M quantization.
For coding workloads, Gemma 2 9B on Mac Studio M3 Ultra 256GB receives a B grade with 80.7 tok/s and 8K context.
On Mac Studio M3 Ultra 256GB, 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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/gemma-2-9b-on-m3-ultra-256gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
5.0 GB |
| Medium |
| C52 |
Q4_K_M | 4 | 5.5 GB | Medium | C52 |
Q5_K_M | 5 | 6.5 GB | High | C52 |
Q6_K | 6 | 7.4 GB | High | C52 |
Q8_0 | 8 | 9.6 GB | Very High | C52 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | C52 |
Not always. Mac Studio M3 Ultra 256GB 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.