Phi-4-reasoning-plus 14B needs ~19.8 GB VRAM. Mac Studio M2 Ultra 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
55.6 tok/s
TTFT
3480 ms
Safe context
33K
Memory
19.8 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 | 55.6 tok/s | 1898 ms | 33K |
| Coding | S | Runs well | 55.6 tok/s | 3480 ms | 33K |
| Agentic Coding | S | Runs well | 55.6 tok/s | 5062 ms | 33K |
| Reasoning | S | Runs well | 55.6 tok/s | 4113 ms | 33K |
| RAG | S | Runs well | 55.6 tok/s | 6328 ms | 33K |
How Phi-4-reasoning-plus 14B (14.699999809265137B params) fits at each quantization level on Mac Studio M2 Ultra 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.7 GB | Low | A82 |
Q3_K_S | 3 | 7.2 GB | Low | A82 |
NVFP4 | 4 |
Copy-paste commands to run Phi-4-reasoning-plus 14B on your machine.
Run
ollama run phi4-reasoningYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 70.2 tok/s | |
| Qwen 3.5 27B | 27B | S | 30.4 tok/s |
Yes, Mac Studio M2 Ultra 64GB can run Phi-4-reasoning-plus 14B with a S grade (Runs well). Expected decode speed: 55.6 tok/s.
Phi-4-reasoning-plus 14B (14.699999809265137B parameters) requires approximately 19.8 GB of memory with Q4_K_M quantization.
The recommended quantization for Phi-4-reasoning-plus 14B is Q4_K_M, which balances quality and memory efficiency.
On Mac Studio M2 Ultra 64GB, Phi-4-reasoning-plus 14B achieves approximately 55.6 tokens per second decode speed with a time-to-first-token of 3480ms using Q4_K_M quantization.
For coding workloads, Phi-4-reasoning-plus 14B on Mac Studio M2 Ultra 64GB receives a S grade with 55.6 tok/s and 33K context.
On Mac Studio M2 Ultra 64GB, Phi-4-reasoning-plus 14B can safely use up to 33K tokens of context. The model's official context limit is 33K, 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/phi-4-reasoning-plus-14b-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:
8.2 GB |
| Medium |
| A82 |
Q4_K_M | 4 | 9.0 GB | Medium | A83 |
Q5_K_M | 5 | 10.6 GB | High | A83 |
Q6_K | 6 | 12.1 GB | High | A83 |
Q8_0 | 8 | 15.7 GB | Very High | A85 |
F16Best for your GPU | 16 | 30.1 GB | Maximum | S88 |
| Qwen 3.6 27B | 27B | S | 23.1 tok/s |
| Qwen 3.6 35B A3B | 35B | S | 59 tok/s |
| Qwen3-VL 30B A3B Instruct | 30B | S | 72.6 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.