RX 7900 XTX 24GBBest value
C99.4 tok/s decode
~$999 MSRP
Can it run?
Too heavy
Using Q4_K_M in vLLM
Fit status
Too heavy
Decode
27.6 tok/s
TTFT
7012 ms
Safe context
6K
Memory
22.3 GB / 8.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | F | Too heavy | 27.6 tok/s | 10199 ms | 11K |
| Chat | F | Too heavy | 27.6 tok/s | 3825 ms | 4K |
| Coding | F | Too heavy | 27.6 tok/s | 7012 ms | 6K |
| RAG | F | Too heavy | 27.6 tok/s | 12749 ms | 11K |
| Reasoning | F | Too heavy | 27.6 tok/s | 8287 ms | 6K |
How Qwen3-VL 30B A3B Instruct (30B params) fits at each quantization level on RTX 4060 Laptop 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.7 GB | Low | F0 |
Q3_K_S | 3 | 14.7 GB | Low | F0 |
NVFP4 | 4 | 16.8 GB | Medium | F0 |
Q4_K_M | 4 | 18.3 GB | Medium | F0 |
Q5_K_M | 5 | 21.6 GB | High | F0 |
Q6_K | 6 | 24.6 GB | High | F0 |
Q8_0 | 8 | 32.1 GB | Very High | F0 |
F16 | 16 | 61.5 GB | Maximum | F0 |
Upgrade options
~$999 MSRP
~$1,099 MSRP
RTX 5090 32GBNVIDIA upgrade~$1,999 MSRP