Raises estimated decode speed by about 46%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
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VOOZH | about |
Phi 4 reasoning vision 15B needs ~22.2 GB VRAM. MacBook Pro M4 Max 96GB has 69.1 GB. With Q4_K_M quantization, expect ~35 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
34.7 tok/s
TTFT
5573 ms
Safe context
443K
Memory
22.2 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 | C | Runs well | 34.7 tok/s | 3040 ms | 443K |
| Coding | C | Runs well | 34.7 tok/s | 5573 ms | 443K |
| Agentic Coding | C | Runs well | 34.7 tok/s | 8107 ms | 443K |
| Reasoning | C | Runs well | 34.7 tok/s | 6587 ms | 443K |
| RAG | C | Runs well | 34.7 tok/s | 10133 ms | 443K |
How Phi 4 reasoning vision 15B (15B params) fits at each quantization level on MacBook Pro M4 Max 96GB (69.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | C40 |
Q3_K_S | 3 | 7.4 GB | Low | C40 |
NVFP4 | 4 | 8.4 GB | Medium | C41 |
Q4_K_M | 4 | 9.2 GB | Medium | C41 |
Q5_K_M | 5 | 10.8 GB | High | C41 |
Q6_K | 6 | 12.3 GB | High | C41 |
Q8_0 | 8 | 16.1 GB | Very High | C42 |
F16Best for your GPU | 16 | 30.7 GB | Maximum | C45 |
Copy-paste commands to run Phi 4 reasoning vision 15B on your machine.
Run
lms load hf-jamesburton--phi-4-reasoning-vision-15b-gguf && lms server startUpgrade options
Raises estimated decode speed by about 46%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Raises estimated decode speed by about 39%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP