MacBook Pro M3 Max 128GBBudget pick
C240 tok/s decode
~$2,499 MSRP
Can it run?
Runs well
Using Q4_K_M in Ollama
Fit status
Runs well
Decode
2412.0 tok/s
TTFT
350 ms
Safe context
117K
Memory
10.9 GB / 80.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | C | Runs well | 2814.0 tok/s | 350 ms | 235K |
| Chat | C | Runs well | 2814.0 tok/s | 350 ms | 59K |
| Coding | C | Runs well | 2412.0 tok/s | 350 ms | 117K |
| RAG | C | Runs well | 2814.0 tok/s | 350 ms | 235K |
| Reasoning | C | Runs well | 2814.0 tok/s | 350 ms | 117K |
How Qwen2.5 1.5B Instruct (1.5B params) fits at each quantization level on NVIDIA H100 80GB (80.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.6 GB | Low | D30 |
Q3_K_S | 3 | 0.7 GB | Low | D30 |
NVFP4 | 4 |
Upgrade options
~$2,499 MSRP
~$3,999 MSRP
0.8 GB |
| Medium |
| D30 |
Q4_K_M | 4 | 0.9 GB | Medium | D30 |
Q5_K_M | 5 | 1.1 GB | High | D30 |
Q6_K | 6 | 1.2 GB | High | D30 |
Q8_0 | 8 | 1.6 GB | Very High | D30 |
F16Best for your GPU | 16 | 3.1 GB | Maximum | D30 |
~$3,999 MSRP