MacBook Pro M4 Pro 64GBBudget pick
C134.6 tok/s decode
~$1,599 MSRP
Can it run?
Runs well
Using Q6_K in Ollama
Fit status
Runs well
Decode
836.3 tok/s
TTFT
350 ms
Safe context
84K
Memory
7.6 GB / 40.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | C | Runs well | 836.3 tok/s | 350 ms | 168K |
| Chat | C | Runs well | 836.3 tok/s | 350 ms | 42K |
| Coding | C | Runs well | 836.3 tok/s | 350 ms | 84K |
| RAG | C | Runs well | 836.3 tok/s | 421 ms | 168K |
| Reasoning | C | Runs well | 836.3 tok/s | 350 ms | 84K |
How gemma 2 2b it (2B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.8 GB | Low | D30 |
Q3_K_S | 3 | 1.0 GB | Low | D30 |
NVFP4 | 4 | 1.1 GB | Medium | D30 |
Q4_K_M | 4 | 1.2 GB | Medium | D30 |
Q5_K_M | 5 | 1.4 GB | High | D30 |
Q6_K | 6 | 1.6 GB | High | D30 |
Q8_0 | 8 | 2.1 GB | Very High | D31 |
F16Best for your GPU | 16 | 4.1 GB | Maximum | D32 |
huggingface-cli download hf-bartowski--gemma-2-2b-it-ggufUpgrade options
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