Can Phi-4 14B run on MacBook Air M4 24GB?
YES — Tight Fit
Phi-4 14B needs ~15.1 GB VRAM. MacBook Air M4 24GB has 17.3 GB. With Q4_K_M quantization, expect ~10 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
Tight fit
Decode
9.6 tok/s
TTFT
20228 ms
Safe context
16K
Memory
15.1 GB / 17.3 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 | 9.6 tok/s | 11034 ms | 16K |
| Coding | A | Tight fit | 10.1 tok/s | 19136 ms | 16K |
| Agentic Coding | A | Runs with offload (needs ~0.4 GB host RAM) | 8.7 tok/s | 32223 ms | 16K |
| Reasoning | A | Tight fit | 9.6 tok/s | 23906 ms | 16K |
| RAG | A | Runs with offload (needs ~0.4 GB host RAM) | 8.7 tok/s | 40278 ms | 16K |
Quantization options
How Phi-4 14B (14B params) fits at each quantization level on MacBook Air M4 24GB (17.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | A80 |
Q3_K_S | 3 | 6.9 GB | Low | A81 |
NVFP4 | 4 | 7.8 GB | Medium | A82 |
Q4_K_M | 4 | 8.5 GB | Medium | A83 |
Q5_K_M | 5 | 10.1 GB | High | A83 |
Q6_KBest for your GPU | 6 | 11.5 GB | High | A82 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Get started
Copy-paste commands to run Phi-4 14B on your machine.
Run
ollama run phi4Your hardware
More models your MacBook Air M4 24GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 24B | A | 7.3 tok/s | ||
| 24B | A | 7.3 tok/s | ||
| 14.7B | S | 9.4 tok/s | ||
| 24B | B | 7.3 tok/s | ||
| 21B | A | 14.4 tok/s |
Frequently asked questions
Can MacBook Air M4 24GB run Phi-4 14B?
Yes, MacBook Air M4 24GB can run Phi-4 14B with a A grade (Tight fit). Expected decode speed: 10.1 tok/s.
How much VRAM does Phi-4 14B need?
Phi-4 14B (14B parameters) requires approximately 15.1 GB of memory with Q4_K_M quantization.
What is the best quantization for Phi-4 14B?
The recommended quantization for Phi-4 14B is Q4_K_M, which balances quality and memory efficiency.
What speed will Phi-4 14B run at on MacBook Air M4 24GB?
On MacBook Air M4 24GB, Phi-4 14B achieves approximately 10.1 tokens per second decode speed with a time-to-first-token of 19136ms using Q4_K_M quantization.
Can MacBook Air M4 24GB run Phi-4 14B for coding?
For coding workloads, Phi-4 14B on MacBook Air M4 24GB receives a A grade with 10.1 tok/s and 16K context.
What context window can Phi-4 14B use on MacBook Air M4 24GB?
On MacBook Air M4 24GB, Phi-4 14B can safely use up to 16K tokens of context. The model's official context limit is 16K, but available memory constrains the safe maximum.
Is unified memory on MacBook Air M4 24GB as fast as VRAM for Phi-4 14B?
Not always. MacBook Air M4 24GB 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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