Can Phi-4 Mini Reasoning 4B run on Mac mini M4 32GB?
YES — Runs Great
Phi-4 Mini Reasoning 4B needs ~8.1 GB VRAM. Mac mini M4 32GB has 23.0 GB. With Q4_K_M quantization, expect ~37 tok/s.
Operating mode
Choose the run profile you care about
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
36.9 tok/s
TTFT
5252 ms
Safe context
131K
Memory
8.1 GB / 23.0 GB
Memory breakdown
See how fast it feels
What limits this setup
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.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 36.9 tok/s | 2865 ms | 131K |
| Coding | A | Runs well | 36.9 tok/s | 5252 ms | 131K |
| Agentic Coding | A | Runs well | 36.9 tok/s | 7639 ms | 131K |
| Reasoning | A | Runs well | 36.9 tok/s | 6207 ms | 131K |
| RAG | A | Runs well | 36.9 tok/s | 9549 ms | 131K |
Quantization options
How Phi-4 Mini Reasoning 4B (3.799999952316284B params) fits at each quantization level on Mac mini M4 32GB (23.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.5 GB | Low | A81 |
Q3_K_S | 3 | 1.9 GB | Low | A81 |
NVFP4 | 4 | 2.1 GB | Medium | A81 |
Q4_K_M | 4 | 2.3 GB | Medium | A81 |
Q5_K_M | 5 | 2.7 GB | High | A82 |
Q6_K | 6 | 3.1 GB | High | A82 |
Q8_0 | 8 | 4.1 GB | Very High | A82 |
F16Best for your GPU | 16 | 7.8 GB | Maximum | A85 |
Get started
Copy-paste commands to run Phi-4 Mini Reasoning 4B on your machine.
Run
ollama run phi4-miniYour hardware
More models your Mac mini M4 32GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | A | 11.7 tok/s | ||
| 27B | S | 8.6 tok/s | ||
| 27B | S | 7.1 tok/s | ||
| 30B | S | 12.4 tok/s | ||
| 9B | S | 15.6 tok/s |
Frequently asked questions
Can Mac mini M4 32GB run Phi-4 Mini Reasoning 4B?
Yes, Mac mini M4 32GB can run Phi-4 Mini Reasoning 4B with a A grade (Runs well). Expected decode speed: 36.9 tok/s.
How much VRAM does Phi-4 Mini Reasoning 4B need?
Phi-4 Mini Reasoning 4B (3.799999952316284B parameters) requires approximately 8.1 GB of memory with Q4_K_M quantization.
What is the best quantization for Phi-4 Mini Reasoning 4B?
The recommended quantization for Phi-4 Mini Reasoning 4B is Q4_K_M, which balances quality and memory efficiency.
What speed will Phi-4 Mini Reasoning 4B run at on Mac mini M4 32GB?
On Mac mini M4 32GB, Phi-4 Mini Reasoning 4B achieves approximately 36.9 tokens per second decode speed with a time-to-first-token of 5252ms using Q4_K_M quantization.
Can Mac mini M4 32GB run Phi-4 Mini Reasoning 4B for coding?
For coding workloads, Phi-4 Mini Reasoning 4B on Mac mini M4 32GB receives a A grade with 36.9 tok/s and 131K context.
What context window can Phi-4 Mini Reasoning 4B use on Mac mini M4 32GB?
On Mac mini M4 32GB, Phi-4 Mini Reasoning 4B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Is unified memory on Mac mini M4 32GB as fast as VRAM for Phi-4 Mini Reasoning 4B?
Not always. Mac mini M4 32GB 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.
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<iframe src="https://willitrunai.com/embed/phi-4-mini-reasoning-on-m4-mini-32gb" 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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