Qwen3-VL 30B A3B Instruct needs ~31.8 GB VRAM. RTX PRO 6000 Blackwell Server Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~159 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
159.4 tok/s
TTFT
1214 ms
Safe context
256K
Memory
31.8 GB / 96.0 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 | 159.4 tok/s | 662 ms | 256K |
| Coding | S | Runs well | 159.4 tok/s | 1214 ms | 256K |
| Agentic Coding | S | Runs well | 159.4 tok/s | 1766 ms | 256K |
| Reasoning | S | Runs well | 159.4 tok/s | 1435 ms | 256K |
| RAG | S | Runs well | 159.4 tok/s | 2208 ms | 256K |
Inference speed
Estimated decode speed (tokens/sec) for Qwen3-VL 30B A3B Instruct at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~143 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
 RTX 5090 32GB | 32 GB | Q4_K_M | 142.7 | Fits |
| RTX 4090 24GB | 24 GB | Q4_K_M | 119.8 | Offloads |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 108.1 | Offloads |
| RTX 3090 24GB | 24 GB | Q4_K_M | 102.5 | Offloads |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 87.1 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 72.6 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 68.8 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 53.8 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 53.8 | Fits |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 37.5 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 34.4 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 32.9 | Fits |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 23.7 | Too big |
| RTX 4070 12GB | 12 GB | Q4_K_M | 8.3 | Too big |
| RTX 3060 12GB | 12 GB | Q4_K_M | 5.2 | Too big |
| RTX 4060 8GB | 8 GB | Q4_K_M | 3.5 | Too big |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How Qwen3-VL 30B A3B Instruct (30B params) fits at each quantization level on RTX PRO 6000 Blackwell Server Edition 96GB (96.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.7 GB | Low | A82 |
Q3_K_S | 3 | 14.7 GB | Low | A82 |
NVFP4 | 4 | 16.8 GB | Medium | A82 |
Q4_K_M | 4 | 18.3 GB | Medium | A83 |
Q5_K_M | 5 | 21.6 GB | High | A83 |
Q6_K | 6 | 24.6 GB | High | A84 |
Q8_0 | 8 | 32.1 GB | Very High | A85 |
F16Best for your GPU | 16 | 61.5 GB | Maximum | S90 |
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 |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 154.2 tok/s | |
| Qwen 3.5 122B A10B | 122B | S | 41 tok/s | |
| Qwen 3.6 35B A3B | 35B | S | 129.6 tok/s |
Yes, RTX PRO 6000 Blackwell Server Edition 96GB can run Qwen3-VL 30B A3B Instruct with a S grade (Runs well). Expected decode speed: 159.4 tok/s.
Qwen3-VL 30B A3B Instruct (30B parameters) requires approximately 31.8 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 RTX PRO 6000 Blackwell Server Edition 96GB, Qwen3-VL 30B A3B Instruct achieves approximately 159.4 tokens per second decode speed with a time-to-first-token of 1214ms using Q4_K_M quantization.
For coding workloads, Qwen3-VL 30B A3B Instruct on RTX PRO 6000 Blackwell Server Edition 96GB receives a S grade with 159.4 tok/s and 256K context.
On RTX PRO 6000 Blackwell Server Edition 96GB, 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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/qwen-3-vl-30b-a3b-on-rtx-pro-6000-blackwell-server-96gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: