MacBook Pro M3 Max 128GBBudget pick
C5.5 tok/s decode
~$2,499 MSRP
Can it run?
Runs with offload
Using Q4_K_M in vLLM
Fit status
Runs with offload
Decode
10.7 tok/s
TTFT
18169 ms
Safe context
16K
Memory
64.0 GB / 64.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | D | Very compromised (needs ~6.6 GB host RAM) | 9.3 tok/s | 30264 ms | 27K |
| Chat | C | Tight fit | 10.7 tok/s | 9910 ms | 9K |
| Coding | C | Runs with offload | 10.7 tok/s | 18169 ms | 16K |
| RAG | D | Very compromised (needs ~6.6 GB host RAM) | 9.3 tok/s | 37830 ms | 27K |
| Reasoning | C | Runs with offload | 10.7 tok/s | 21472 ms | 16K |
How Qwen 2.5 VL 72B (72B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 28.1 GB | Low | D39 |
Q3_K_S | 3 | 35.3 GB | Low | C41 |
NVFP4 | 4 | 40.3 GB | Medium | C43 |
Q4_K_MBest for your GPU | 4 | 43.9 GB | Medium | C44 |
Q5_K_M | 5 | 51.8 GB | High | C44 |
Q6_K | 6 | 59.0 GB | High | C44 |
Q8_0 | 8 | 77.0 GB | Very High | F0 |
F16 | 16 | 147.6 GB | Maximum | F0 |
ollama run qwen-2.5-vl-72bhuggingface-cli download qwen-2.5-vl-72bUpgrade options
~$2,499 MSRP
~$3,999 MSRP
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