MacBook Pro M4 32GBBest value
C11.9 tok/s decode
~$799 MSRP
Can it run?
Too heavy
Using Q4_K_M in Ollama
Fit status
Too heavy
Decode
74.8 tok/s
TTFT
2590 ms
Safe context
12K
Memory
22.2 GB / 16.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | F | Too heavy | 74.8 tok/s | 3767 ms | 23K |
| Chat | F | Too heavy | 74.8 tok/s | 1413 ms | 6K |
| Coding | F | Too heavy | 74.8 tok/s | 2590 ms | 12K |
| RAG | F | Too heavy | 74.8 tok/s | 4709 ms | 23K |
| Reasoning | F | Too heavy | 74.8 tok/s | 3061 ms | 12K |
How Qwen3-Coder 30B A3B Instruct (30.5B params) fits at each quantization level on RTX 4070 Ti Super 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.9 GB | Low | C45 |
Q3_K_S | 3 | 14.9 GB | Low | C45 |
NVFP4 | 4 | 17.1 GB | Medium | F0 |
Q4_K_M | 4 | 18.6 GB | Medium | F0 |
Q5_K_M | 5 | 22.0 GB | High | F0 |
Q6_K | 6 | 25.0 GB | High | F0 |
Q8_0 | 8 | 32.6 GB | Very High | F0 |
F16 | 16 | 62.5 GB | Maximum | F0 |
Upgrade options
~$799 MSRP
~$1,099 MSRP
RTX 5090 32GBNVIDIA upgrade~$1,999 MSRP