Will It Run AI

Can Qwen 3 32B run on NVIDIA A16 64GB?

YES — Runs Great

S89Excellent
Estimated from fit model

Qwen 3 32B needs ~31.0 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~26 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: BasicBottleneck: 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) 31.0 GB, 26.1 tok/s, Runs well
31.0 GB required64.0 GB available
48% VRAM used

Fit status

Runs well

Decode

26.1 tok/s

TTFT

7425 ms

Safe context

131K

Memory

31.0 GB / 64.0 GB

Memory breakdown

Weights19.5 GB
KV Cache3.9 GB
Runtime1.2 GB
Headroom6.4 GB

See how fast it feels

See how fast it feelsQwen 3 32B 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: 26.1 tok/s decode · 7.4s TTFT (warm) · 65 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 well24.0 tok/s4405 ms131K
CodingSRuns well26.1 tok/s7425 ms131K
Agentic CodingSRuns well26.1 tok/s10800 ms131K
ReasoningSRuns well26.1 tok/s8775 ms131K
RAGSRuns well26.1 tok/s13500 ms131K

Quantization options

How Qwen 3 32B (32B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
12.5 GB
LowA83
Q3_K_S
3
15.7 GB
LowA84
NVFP4
4
17.9 GB
MediumA84
Q4_K_M
4
19.5 GB
MediumA84
Q5_K_M
5
23.0 GB
HighS85
Q6_K
6
26.2 GB
HighS86
Q8_0Best for your GPU
8
34.2 GB
Very HighS88
F16
16
65.6 GB
MaximumF0

Get started

Copy-paste commands to run Qwen 3 32B on your machine.

Run

ollama run qwen3:32b

Your hardware

More models your NVIDIA A16 64GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen 3.6 35B A3B35BS59.5 tok/s
AlibabaQwen 3.5 35B A3B35BS64.7 tok/s

Frequently asked questions

Can NVIDIA A16 64GB run Qwen 3 32B?

Yes, NVIDIA A16 64GB can run Qwen 3 32B with a S grade (Runs well). Expected decode speed: 26.1 tok/s.

How much VRAM does Qwen 3 32B need?

Qwen 3 32B (32B parameters) requires approximately 31.0 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3 32B?

The recommended quantization for Qwen 3 32B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3 32B run at on NVIDIA A16 64GB?

On NVIDIA A16 64GB, Qwen 3 32B achieves approximately 26.1 tokens per second decode speed with a time-to-first-token of 7425ms using Q4_K_M quantization.

Can NVIDIA A16 64GB run Qwen 3 32B for coding?

For coding workloads, Qwen 3 32B on NVIDIA A16 64GB receives a S grade with 26.1 tok/s and 131K context.

What context window can Qwen 3 32B use on NVIDIA A16 64GB?

On NVIDIA A16 64GB, Qwen 3 32B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for NVIDIA A16 64GBSee all hardware for Qwen 3 32B
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