Raises estimated decode speed by about 89%.
~$599 MSRP
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VOOZH | about |
Phi 3 Medium 14B needs ~15.9 GB VRAM. MacBook Pro M1 Pro 32GB has 23.0 GB. With Q4_K_M quantization, expect ~16 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
16.4 tok/s
TTFT
11831 ms
Safe context
53K
Memory
15.9 GB / 23.0 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 | B | Runs well | 16.4 tok/s | 6453 ms | 53K |
| Coding | B | Runs well | 16.4 tok/s | 11831 ms | 53K |
| Agentic Coding | B | Tight fit | 16.4 tok/s | 17208 ms | 53K |
| Reasoning | B | Runs well | 16.4 tok/s | 13982 ms | 53K |
| RAG | B | Tight fit | 16.4 tok/s | 21510 ms | 53K |
How Phi 3 Medium 14B (14B params) fits at each quantization level on MacBook Pro M1 Pro 32GB (23.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | B57 |
Q3_K_S | 3 | 6.9 GB | Low | B58 |
NVFP4 | 4 | 7.8 GB | Medium | B59 |
Q4_K_M | 4 | 8.5 GB | Medium | B59 |
Q5_K_M | 5 | 10.1 GB | High | B60 |
Q6_K | 6 | 11.5 GB | High | B61 |
Q8_0Best for your GPU | 8 | 15.0 GB | Very High | B61 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Copy-paste commands to run Phi 3 Medium 14B on your machine.
Run
ollama run phi3:mediumUpgrade options
Raises estimated decode speed by about 89%.
~$599 MSRP
Raises estimated decode speed by about 98%.
~$2,499 MSRP