MacBook Pro M3 Max 128GBBudget pick
C14.9 tok/s decode
~$2,499 MSRP
Can it run?
Too heavy
Using Q4_K_M in Ollama
Fit status
Too heavy
Decode
28.6 tok/s
TTFT
6766 ms
Safe context
9K
Memory
54.0 GB / 32.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | F | Too heavy | 28.6 tok/s | 9841 ms | 19K |
| Chat | F | Too heavy | 28.6 tok/s | 3690 ms | 5K |
| Coding | F | Too heavy | 28.6 tok/s | 6766 ms | 9K |
| RAG | F | Too heavy | 28.6 tok/s | 12302 ms | 19K |
| Reasoning | F | Too heavy | 28.6 tok/s | 7996 ms | 9K |
How Qwen3-Coder-Next (80B params) fits at each quantization level on RTX 5000 Ada 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 31.2 GB | Low | C45 |
Q3_K_S | 3 | 39.2 GB | Low | F0 |
NVFP4 | 4 | 44.8 GB | Medium | F0 |
Q4_K_M | 4 | 48.8 GB | Medium | F0 |
Q5_K_M | 5 | 57.6 GB | High | F0 |
Q6_K | 6 | 65.6 GB | High | F0 |
Q8_0 | 8 | 85.6 GB | Very High | F0 |
F16 | 16 | 164.0 GB | Maximum | F0 |
Upgrade options
~$2,499 MSRP
~$2,499 MSRP
NVIDIA A100 80GBBiggest leap~$15,000 MSRP
NVIDIA A800 80GBNVIDIA upgrade