Can Qwen 3 32B run on NVIDIA A100 40GB?

YES — Runs Great

S97Excellent

Estimated from fit model

Qwen 3 32B needs ~28.6 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~67 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: Balanced

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, 72.8 tok/s, Runs well

28.6 GB required40.0 GB available

72% VRAM used

Fit status

Runs well

Decode

72.8 tok/s

TTFT

2660 ms

Safe context

63K

Memory

28.6 GB / 40.0 GB

Memory breakdown

Weights19.5 GB

KV Cache3.9 GB

Runtime1.2 GB

Headroom4.0 GB

See how fast it feels

See how fast it feelsQwen 3 32B on NVIDIA A100 40GB
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: 72.8 tok/s decode · 2.7s TTFT (warm) · 182 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	S	Runs well	72.8 tok/s	1451 ms	63K
Coding	S	Runs well	66.9 tok/s	2893 ms	63K
Agentic Coding	S	Runs well	72.8 tok/s	3870 ms	63K
Reasoning	S	Runs well	72.8 tok/s	3144 ms	63K
RAG	S	Runs well	72.8 tok/s	4837 ms	63K

Quantization options

How Qwen 3 32B (32B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	12.5 GB	Low	S86
Q3_K_S	3	15.7 GB	Low	S88
NVFP4	4	17.9 GB	Medium	S88
Q4_K_M	4	19.5 GB	Medium	S89
Q5_K_M	5	23.0 GB	High	S90
Q6_KBest for your GPU	6	26.2 GB	High	S89
Q8_0	8	34.2 GB	Very High	F0
F16	16	65.6 GB	Maximum	F0

Get started

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

Run

ollama run qwen3:32b

Your hardware

More models your NVIDIA A100 40GB can run

Model	Params	Grade	Decode	Capabilities
Qwen 3.6 35B A3B	35B	S	166 tok/s
Qwen 3.5 35B A3B	35B	S	180.5 tok/s

Frequently asked questions

Can NVIDIA A100 40GB run Qwen 3 32B?

Yes, NVIDIA A100 40GB can run Qwen 3 32B with a S grade (Runs well). Expected decode speed: 66.9 tok/s.

How much VRAM does Qwen 3 32B need?

Qwen 3 32B (32B parameters) requires approximately 28.6 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 A100 40GB?

On NVIDIA A100 40GB, Qwen 3 32B achieves approximately 66.9 tokens per second decode speed with a time-to-first-token of 2893ms using Q4_K_M quantization.

Can NVIDIA A100 40GB run Qwen 3 32B for coding?

For coding workloads, Qwen 3 32B on NVIDIA A100 40GB receives a S grade with 66.9 tok/s and 63K context.

What context window can Qwen 3 32B use on NVIDIA A100 40GB?

On NVIDIA A100 40GB, Qwen 3 32B can safely use up to 63K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for NVIDIA A100 40GB See all hardware for Qwen 3 32B

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