Qwen 3 32B needs ~31.2 GB VRAM. Mac Studio M2 Ultra 64GB has 46.1 GB. With Q4_K_M quantization, expect ~26 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
7489 ms
Safe context
77K
Memory
31.2 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 | S | Runs well | 25.9 tok/s | 4085 ms | 77K |
| Coding | S | Runs well | 25.9 tok/s | 7489 ms | 77K |
| Agentic Coding | S | Runs well | 25.9 tok/s | 10893 ms | 77K |
| Reasoning | S | Runs well | 25.9 tok/s | 8851 ms | 77K |
| RAG | S | Runs well | 25.9 tok/s | 13617 ms | 77K |
How Qwen 3 32B (32B params) fits at each quantization level on Mac Studio M2 Ultra 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | S85 |
Q3_K_S | 3 | 15.7 GB | Low | S86 |
NVFP4 | 4 |
Copy-paste commands to run Qwen 3 32B on your machine.
Run
ollama run qwen3:32bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3.6 35B A3B | 35B | S | 59 tok/s | |
|
Yes, Mac Studio M2 Ultra 64GB can run Qwen 3 32B with a S grade (Runs well). Expected decode speed: 25.9 tok/s.
Qwen 3 32B (32B parameters) requires approximately 31.2 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 3 32B is Q4_K_M, which balances quality and memory efficiency.
On Mac Studio M2 Ultra 64GB, Qwen 3 32B achieves approximately 25.9 tokens per second decode speed with a time-to-first-token of 7489ms using Q4_K_M quantization.
For coding workloads, Qwen 3 32B on Mac Studio M2 Ultra 64GB receives a S grade with 25.9 tok/s and 77K context.
On Mac Studio M2 Ultra 64GB, Qwen 3 32B can safely use up to 77K tokens of context. The model's official context limit is 131K, 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/qwen-3-32b-on-m2-ultra-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
17.9 GB |
| Medium |
| S87 |
Q4_K_M | 4 | 19.5 GB | Medium | S87 |
Q5_K_M | 5 | 23.0 GB | High | S89 |
Q6_K | 6 | 26.2 GB | High | S89 |
Q8_0Best for your GPU | 8 | 34.2 GB | Very High | S89 |
F16 | 16 | 65.6 GB | Maximum | F0 |
| 35B |
| S |
| 64.1 tok/s |
Not always. Mac Studio M2 Ultra 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.