Raises estimated decode speed by about 383%.
Adds memory headroom for longer context windows and future model growth.
~$12,000 MSRP
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VOOZH | about |
Gemma 2 27B needs ~39.0 GB VRAM. MacBook Pro M4 Max 96GB has 69.1 GB. With Q4_K_M quantization, expect ~27 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
26.6 tok/s
TTFT
7278 ms
Safe context
8K
Memory
39.0 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 | B | Runs well | 26.6 tok/s | 3970 ms | 8K |
| Coding | B | Runs well | 26.6 tok/s | 7278 ms | 8K |
| Agentic Coding | A | Runs well | 26.6 tok/s | 10587 ms | 8K |
| Reasoning | B | Runs well | 26.6 tok/s | 8602 ms | 8K |
| RAG | A | Runs well | 26.6 tok/s | 13233 ms | 8K |
How Gemma 2 27B (27B params) fits at each quantization level on MacBook Pro M4 Max 96GB (69.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 10.5 GB | Low | B61 |
Q3_K_S | 3 | 13.2 GB | Low | B61 |
NVFP4 | 4 | 15.1 GB | Medium | B61 |
Q4_K_M | 4 | 16.5 GB | Medium | B62 |
Q5_K_M | 5 | 19.4 GB | High | B62 |
Q6_K | 6 | 22.1 GB | High | B63 |
Q8_0 | 8 | 28.9 GB | Very High | B64 |
F16Best for your GPU | 16 | 55.4 GB | Maximum | B67 |
Copy-paste commands to run Gemma 2 27B on your machine.
Run
ollama run gemma2:27bUpgrade options
Raises estimated decode speed by about 383%.
Adds memory headroom for longer context windows and future model growth.
~$12,000 MSRP
Raises estimated decode speed by about 155%.
~$15,000 MSRP