Can Qwen3-VL 30B A3B Instruct run on RTX 6000 Ada 48GB?
YES — Runs Great
Qwen3-VL 30B A3B Instruct needs ~27.0 GB VRAM. RTX 6000 Ada 48GB has 48.0 GB. With Q4_K_M quantization, expect ~94 tok/s.
Operating mode
Choose the run profile you care about
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
93.6 tok/s
TTFT
2069 ms
Safe context
246K
Memory
27.0 GB / 48.0 GB
Memory breakdown
See how fast it feels
What limits this setup
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 93.6 tok/s | 1129 ms | 246K |
| Coding | S | Runs well | 93.6 tok/s | 2069 ms | 246K |
| Agentic Coding | S | Runs well | 93.6 tok/s | 3010 ms | 246K |
| Reasoning | S | Runs well | 93.6 tok/s | 2445 ms | 246K |
| RAG | S | Runs well | 93.6 tok/s | 3762 ms | 246K |
Quantization options
How Qwen3-VL 30B A3B Instruct (30B params) fits at each quantization level on RTX 6000 Ada 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.7 GB | Low | S86 |
Q3_K_S | 3 | 14.7 GB | Low | S87 |
NVFP4 | 4 | 16.8 GB | Medium | S87 |
Q4_K_M | 4 | 18.3 GB | Medium | S88 |
Q5_K_M | 5 | 21.6 GB | High | S89 |
Q6_K | 6 | 24.6 GB | High | S90 |
Q8_0Best for your GPU | 8 | 32.1 GB | Very High | S90 |
F16 | 16 | 61.5 GB | Maximum | F0 |
Get started
Copy-paste commands to run Qwen3-VL 30B A3B Instruct on your machine.
Run
lms load Qwen3-VL-30B-A3B-Instruct && lms server startYour hardware
