Qwen3-VL 30B A3B Instruct needs ~41.4 GB VRAM. B100 192GB has 192.0 GB. With Q4_K_M quantization, expect ~799 tok/s.
Operating mode
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
798.7 tok/s
TTFT
350 ms
Safe context
256K
Memory
41.4 GB / 192.0 GB
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 798.7 tok/s | 350 ms | 256K |
| Coding | S | Runs well | 798.7 tok/s | 350 ms | 256K |
| Agentic Coding | S | Runs well | 798.7 tok/s | 353 ms | 256K |
| Reasoning | S | Runs well | 798.7 tok/s | 350 ms | 256K |
| RAG | S | Runs well | 798.7 tok/s | 441 ms | 256K |
How Qwen3-VL 30B A3B Instruct (30B params) fits at each quantization level on B100 192GB (192.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.7 GB | Low | A79 |
Q3_K_S | 3 | 14.7 GB | Low | A79 |
NVFP4 | 4 | 16.8 GB | Medium | A79 |
Q4_K_M | 4 | 18.3 GB | Medium | A80 |
Q5_K_M | 5 | 21.6 GB | High | A80 |
Q6_K | 6 | 24.6 GB | High | A80 |
Q8_0 | 8 | 32.1 GB | Very High | A81 |
F16Best for your GPU | 16 | 61.5 GB | Maximum | A84 |
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
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 123B | S | 77.9 tok/s | ||
| 30.5B | S | 772.3 tok/s | ||
| 122B | S | 205.3 tok/s | ||
| 284B | S | 110 tok/s | ||
| 35B | S | 649 tok/s |
Yes, B100 192GB can run Qwen3-VL 30B A3B Instruct with a S grade (Runs well). Expected decode speed: 798.7 tok/s.
Qwen3-VL 30B A3B Instruct (30B parameters) requires approximately 41.4 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen3-VL 30B A3B Instruct is Q4_K_M, which balances quality and memory efficiency.
On B100 192GB, Qwen3-VL 30B A3B Instruct achieves approximately 798.7 tokens per second decode speed with a time-to-first-token of 350ms using Q4_K_M quantization.
For coding workloads, Qwen3-VL 30B A3B Instruct on B100 192GB receives a S grade with 798.7 tok/s and 256K context.
On B100 192GB, Qwen3-VL 30B A3B Instruct can safely use up to 256K tokens of context. The model's official context limit is 256K, but available memory constrains the safe maximum.
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<iframe src="https://willitrunai.com/embed/qwen-3-vl-30b-a3b-on-b100-192gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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