MacBook Pro M2 Max 32GBBudget pick
C109.6 tok/s decode
~$1,999 MSRP
Can it run?
Runs well
Using Q5_K_M in Ollama
Fit status
Runs well
Decode
235.7 tok/s
TTFT
821 ms
Safe context
52K
Memory
6.2 GB / 20.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | C | Runs well | 235.7 tok/s | 1195 ms | 102K |
| Chat | C | Runs well | 235.7 tok/s | 448 ms | 26K |
| Coding | C | Runs well | 235.7 tok/s | 821 ms | 52K |
| RAG | C | Runs well | 235.7 tok/s | 1493 ms | 102K |
| Reasoning | C | Runs well | 235.7 tok/s | 971 ms | 52K |
How Llama 3.2 3B Instruct (3B params) fits at each quantization level on RTX A4500 20GB (20.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.2 GB | Low | D31 |
Q3_K_S | 3 | 1.5 GB | Low | D31 |
NVFP4 | 4 | 1.7 GB | Medium | D31 |
Q4_K_M | 4 | 1.8 GB | Medium | D31 |
Q5_K_M | 5 | 2.2 GB | High | D32 |
Q6_K | 6 | 2.5 GB | High | D32 |
Q8_0 | 8 | 3.2 GB | Very High | D33 |
F16Best for your GPU | 16 | 6.1 GB | Maximum | D36 |
huggingface-cli download hf-bartowski--llama-3-2-3b-instruct-ggufUpgrade options
~$1,999 MSRP
~$2,499 MSRP