Can Qwen3-VL 30B A3B Instruct run on NVIDIA A16 64GB?

YES — Runs Great

S92Excellent
Estimated from fit model

Qwen3-VL 30B A3B Instruct needs ~28.6 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~51 tok/s.

Runtime: vLLMCapacity: RoomyBandwidth: MediumStack: OptimizedBottleneck: Balanced
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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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) 28.6 GB, 55.6 tok/s, Runs well
28.6 GB required64.0 GB available
45% VRAM used

Fit status

Runs well

Decode

55.6 tok/s

TTFT

3481 ms

Safe context

256K

Memory

28.6 GB / 64.0 GB

Memory breakdown

Weights18.3 GB
KV Cache1.5 GB
Runtime2.4 GB
Headroom6.4 GB

See how fast it feels

See how fast it feelsQwen3-VL 30B A3B Instruct on NVIDIA A16 64GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 55.6 tok/s decode · 3.5s TTFT (warm) · 139 tok/s prefill

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

WorkloadGradeFitDecodeTTFTContext
ChatSRuns well55.6 tok/s1898 ms256K
CodingSRuns well51.1 tok/s3785 ms256K
Agentic CodingSRuns well55.6 tok/s5063 ms256K
ReasoningSRuns well55.6 tok/s4113 ms256K
RAGSRuns well55.6 tok/s6328 ms256K

Quantization options

How Qwen3-VL 30B A3B Instruct (30B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
11.7 GB
LowA84
Q3_K_S
3
14.7 GB
LowA85
NVFP4
4
16.8 GB
MediumA85
Q4_K_M
4
18.3 GB
MediumS85
Q5_K_M
5
21.6 GB
HighS86
Q6_K
6
24.6 GB
HighS87
Q8_0Best for your GPU
8
32.1 GB
Very HighS89
F16
16
61.5 GB
MaximumF0

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 start

Your hardware

More models your NVIDIA A16 64GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS53.8 tok/s
AlibabaQwen 3.6 35B A3B35BS45.2 tok/s

Frequently asked questions

Can NVIDIA A16 64GB run Qwen3-VL 30B A3B Instruct?

Yes, NVIDIA A16 64GB can run Qwen3-VL 30B A3B Instruct with a S grade (Runs well). Expected decode speed: 51.1 tok/s.

How much VRAM does Qwen3-VL 30B A3B Instruct need?

Qwen3-VL 30B A3B Instruct (30B parameters) requires approximately 28.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen3-VL 30B A3B Instruct?

The recommended quantization for Qwen3-VL 30B A3B Instruct is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen3-VL 30B A3B Instruct run at on NVIDIA A16 64GB?

On NVIDIA A16 64GB, Qwen3-VL 30B A3B Instruct achieves approximately 51.1 tokens per second decode speed with a time-to-first-token of 3785ms using Q4_K_M quantization.

Can NVIDIA A16 64GB run Qwen3-VL 30B A3B Instruct for coding?

For coding workloads, Qwen3-VL 30B A3B Instruct on NVIDIA A16 64GB receives a S grade with 51.1 tok/s and 256K context.

What context window can Qwen3-VL 30B A3B Instruct use on NVIDIA A16 64GB?

On NVIDIA A16 64GB, 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.

See all results for NVIDIA A16 64GBSee all hardware for Qwen3-VL 30B A3B Instruct
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