MacBook Pro M2 Pro 16GBBudget pick
C89.6 tok/s decode
~$1,999 MSRP
Can it run?
Runs well
Using Q6_K in Ollama
Fit status
Runs well
Decode
369.8 tok/s
TTFT
524 ms
Safe context
34K
Memory
4.6 GB / 10.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | C | Runs well | 369.8 tok/s | 761 ms | 69K |
| Chat | C | Runs well | 369.8 tok/s | 350 ms | 17K |
| Coding | C | Runs well | 369.8 tok/s | 524 ms | 34K |
| RAG | C | Runs well | 369.8 tok/s | 952 ms | 69K |
| Reasoning | C | Runs well | 369.8 tok/s | 619 ms | 34K |
How gemma 2 2b it (2B params) fits at each quantization level on RTX 3080 10GB (10.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.8 GB | Low | D31 |
Q3_K_S | 3 | 1.0 GB | Low | D32 |
NVFP4 | 4 | 1.1 GB | Medium | D32 |
Q4_K_M | 4 | 1.2 GB | Medium | D32 |
Q5_K_M | 5 | 1.4 GB | High | D33 |
Q6_K | 6 | 1.6 GB | High | D33 |
Q8_0 | 8 | 2.1 GB | Very High | D34 |
F16Best for your GPU | 16 | 4.1 GB | Maximum | D38 |
huggingface-cli download hf-bartowski--gemma-2-2b-it-ggufUpgrade options
~$1,999 MSRP