MacBook Pro M3 Max 128GBBest value
C3.7 tok/s decode
~$2,499 MSRP
Can it run?
Too heavy
Using Q3_K_M in Ollama
Fit status
Too heavy
Decode
7.3 tok/s
TTFT
26591 ms
Safe context
5K
Memory
82.4 GB / 24.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | F | Too heavy | 7.3 tok/s | 38678 ms | 8K |
| Chat | F | Too heavy | 7.3 tok/s | 14504 ms | 4K |
| Coding | F | Too heavy | 7.3 tok/s | 26591 ms | 5K |
| RAG | F | Too heavy | 7.3 tok/s | 48347 ms | 8K |
| Reasoning | F | Too heavy | 7.3 tok/s | 31426 ms | 5K |
How Qwen3.5 122B A10B (122B params) fits at each quantization level on NVIDIA A10 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 47.6 GB | Low | F0 |
Q3_K_S | 3 | 59.8 GB | Low | F0 |
NVFP4 | 4 | 68.3 GB | Medium | F0 |
Q4_K_M | 4 | 74.4 GB | Medium | F0 |
Q5_K_M | 5 | 87.8 GB | High | F0 |
Q6_K | 6 | 100.0 GB | High | F0 |
Q8_0 | 8 | 130.5 GB | Very High | F0 |
F16 | 16 | 250.1 GB | Maximum | F0 |
Upgrade options
~$2,499 MSRP
~$8,000 MSRP
NVIDIA H200 141GBNVIDIA upgrade~$30,000 MSRP