Qwen 2.5 72B needs ~60.1 GB VRAM. Mac Studio M3 Ultra 96GB has 69.1 GB. With Q4_K_M quantization, expect ~14 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
Tight fit
Decode
13.8 tok/s
TTFT
14039 ms
Safe context
46K
Memory
60.1 GB / 69.1 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 | A | Tight fit | 13.8 tok/s | 7658 ms | 46K |
| Coding | A | Tight fit | 13.8 tok/s | 14039 ms | 46K |
| Agentic Coding | A | Tight fit | 13.8 tok/s | 20421 ms | 46K |
| Reasoning | A | Tight fit | 13.8 tok/s | 16592 ms | 46K |
| RAG | A | Tight fit | 13.8 tok/s | 25526 ms | 46K |
How Qwen 2.5 72B (72B params) fits at each quantization level on Mac Studio M3 Ultra 96GB (69.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 28.1 GB | Low | A76 |
Q3_K_S | 3 | 35.3 GB | Low | A79 |
NVFP4 | 4 |
Copy-paste commands to run Qwen 2.5 72B on your machine.
Run
ollama run qwen2.5:72bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Command A 111B | 111B | A | 6.8 tok/s | |
 Qwen3-Coder-Next | 80B | S | 37.6 tok/s |
Yes, Mac Studio M3 Ultra 96GB can run Qwen 2.5 72B with a A grade (Tight fit). Expected decode speed: 13.8 tok/s.
Qwen 2.5 72B (72B parameters) requires approximately 60.1 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 2.5 72B is Q4_K_M, which balances quality and memory efficiency.
On Mac Studio M3 Ultra 96GB, Qwen 2.5 72B achieves approximately 13.8 tokens per second decode speed with a time-to-first-token of 14039ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 72B on Mac Studio M3 Ultra 96GB receives a A grade with 13.8 tok/s and 46K context.
On Mac Studio M3 Ultra 96GB, Qwen 2.5 72B can safely use up to 46K 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-2.5-72b-on-m3-ultra-96gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
40.3 GB |
| Medium |
| A79 |
Q4_K_M | 4 | 43.9 GB | Medium | A79 |
Q5_K_MBest for your GPU | 5 | 51.8 GB | High | A79 |
Q6_K | 6 | 59.0 GB | High | F0 |
Q8_0 | 8 | 77.0 GB | Very High | F0 |
F16 | 16 | 147.6 GB | Maximum | F0 |
Not always. Mac Studio M3 Ultra 96GB 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.