RX 7900 XTX 24GBBest value
C31 tok/s decode
~$999 MSRP
Can it run?
Too heavy
Using Q4_K_M in Ollama
Fit status
Too heavy
Decode
4.0 tok/s
TTFT
48450 ms
Safe context
13K
Memory
29.2 GB / 23.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | F | Too heavy | 4.4 tok/s | 63621 ms | 22K |
| Chat | D | Very compromised (needs ~2.7 GB host RAM) | 4.2 tok/s | 24875 ms | 7K |
| Coding | F | Too heavy | 4.0 tok/s | 48450 ms | 13K |
| RAG | F | Too heavy | 4.4 tok/s | 79526 ms | 22K |
| Reasoning | F | Too heavy | 4.4 tok/s | 51692 ms | 13K |
How Qwen 2.5 Coder 32B (32B params) fits at each quantization level on Mac mini M4 32GB (23.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | C41 |
Q3_K_SBest for your GPU | 3 | 15.7 GB | Low | C44 |
Upgrade options
~$999 MSRP
~$1,099 MSRP
| 4 |
17.9 GB |
| Medium |
| C44 |
Q4_K_M | 4 | 19.5 GB | Medium | C44 |
Q5_K_M | 5 | 23.0 GB | High | C44 |
Q6_K | 6 | 26.2 GB | High | F0 |
Q8_0 | 8 | 34.2 GB | Very High | F0 |
F16 | 16 | 65.6 GB | Maximum | F0 |
~$3,999 MSRP
NVIDIA A100 40GBBiggest leap~$10,000 MSRP