MacBook Pro M3 Max 128GBBudget pick
C5.5 tok/s decode
~$2,499 MSRP
Can it run?
Too heavy
Using Q4_K_M in Ollama
Fit status
Too heavy
Decode
15.3 tok/s
TTFT
12617 ms
Safe context
13K
Memory
61.2 GB / 48.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | F | Too heavy | 15.3 tok/s | 18352 ms | 21K |
| Chat | D | Very compromised (needs ~6 GB host RAM) | 13.6 tok/s | 7780 ms | 7K |
| Coding | F | Too heavy | 15.3 tok/s | 12617 ms | 13K |
| RAG | F | Too heavy | 15.3 tok/s | 22940 ms | 21K |
| Reasoning | F | Too heavy | 15.3 tok/s | 14911 ms | 13K |
How Qwen 2.5 72B (72B params) fits at each quantization level on NVIDIA L40 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 28.1 GB | Low | C42 |
Q3_K_SBest for your GPU | 3 | 35.3 GB | Low | C45 |
NVFP4 | 4 | 40.3 GB | Medium | C45 |
Q4_K_M | 4 | 43.9 GB | Medium | C45 |
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