MacBook Pro M3 Max 128GBBudget pick
C5.5 tok/s decode
~$2,499 MSRP
Can it run?
Too heavy
Using Q4_K_M in vLLM
Fit status
Too heavy
Decode
29.7 tok/s
TTFT
6510 ms
Safe context
10K
Memory
61.6 GB / 40.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | F | Too heavy | 29.7 tok/s | 9469 ms | 18K |
| Chat | F | Too heavy | 29.7 tok/s | 3551 ms | 6K |
| Coding | F | Too heavy | 29.7 tok/s | 6510 ms | 10K |
| RAG | F | Too heavy | 29.7 tok/s | 11836 ms | 18K |
| Reasoning | F | Too heavy | 29.7 tok/s | 7693 ms | 10K |
How Qwen 2.5 VL 72B (72B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_KBest for your GPU | 2 | 28.1 GB | Low | C44 |
Q3_K_S | 3 | 35.3 GB | Low | C44 |
NVFP4 | 4 | 40.3 GB | Medium | F0 |
Q4_K_M | 4 | 43.9 GB | Medium | F0 |
Q5_K_M | 5 | 51.8 GB | High | F0 |
Q6_K | 6 | 59.0 GB | High | F0 |
Q8_0 | 8 | 77.0 GB | Very High | F0 |
F16 | 16 | 147.6 GB | Maximum | F0 |
Upgrade options
~$2,499 MSRP
~$2,499 MSRP
NVIDIA GH200 96GBBiggest leap
NVIDIA H20 96GBNVIDIA upgrade