MacBook Pro M3 Max 128GBBest value
D3 tok/s decode
~$2,499 MSRP
Can it run?
Too heavy
Using Q4_K_M in vLLM
Fit status
Too heavy
Decode
18.6 tok/s
TTFT
10426 ms
Safe context
12K
Memory
104.6 GB / 80.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | F | Too heavy | 18.6 tok/s | 15165 ms | 21K |
| Chat | D | Very compromised | 16.1 tok/s | 6571 ms | 7K |
| Coding | F | Too heavy | 18.6 tok/s | 10426 ms | 12K |
| RAG | F | Too heavy | 18.6 tok/s | 18957 ms | 21K |
| Reasoning | F | Too heavy | 18.6 tok/s | 12322 ms | 12K |
How Devstral 2 123B Instruct (123B params) fits at each quantization level on NVIDIA A800 80GB (80.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 48.0 GB | Low | C42 |
Q3_K_SBest for your GPU | 3 | 60.3 GB | Low | C45 |
Upgrade options
~$2,499 MSRP
~$8,000 MSRP
NVIDIA B200 180GBBiggest leap| 4 |
68.9 GB |
| Medium |
| C45 |
Q4_K_M | 4 | 75.0 GB | Medium | C45 |
Q5_K_M | 5 | 88.6 GB | High | F0 |
Q6_K | 6 | 100.9 GB | High | F0 |
Q8_0 | 8 | 131.6 GB | Very High | F0 |
F16 | 16 | 252.2 GB | Maximum | F0 |
~$30,000 MSRP
NVIDIA H200 141GBNVIDIA upgrade~$30,000 MSRP