Will It Run AI

Can Qwen 3 8B run on NVIDIA A16 64GB?

YES — Runs Great

S87Excellent
Estimated from fit model

Qwen 3 8B needs ~14.7 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~103 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) 14.7 GB, 103.1 tok/s, Runs well
14.7 GB required64.0 GB available
23% VRAM used

Fit status

Runs well

Decode

103.1 tok/s

TTFT

1878 ms

Safe context

131K

Memory

14.7 GB / 64.0 GB

Memory breakdown

Weights4.9 GB
KV Cache2.2 GB
Runtime1.2 GB
Headroom6.4 GB

See how fast it feels

See how fast it feelsQwen 3 8B 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: 103.1 tok/s decode · 1.9s TTFT (warm) · 258 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 well103.1 tok/s1024 ms131K
CodingSRuns well103.1 tok/s1878 ms131K
Agentic CodingSRuns well103.1 tok/s2731 ms131K
ReasoningSRuns well103.1 tok/s2219 ms131K
RAGSRuns well103.1 tok/s3414 ms131K

Quantization options

How Qwen 3 8B (8B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.1 GB
LowA80
Q3_K_S
3
3.9 GB
LowA80
NVFP4
4
4.5 GB
MediumA80
Q4_K_M
4
4.9 GB
MediumA80
Q5_K_M
5
5.8 GB
HighA81
Q6_K
6
6.6 GB
HighA81
Q8_0
8
8.6 GB
Very HighA81
F16Best for your GPU
16
16.4 GB
MaximumA82

Get started

Copy-paste commands to run Qwen 3 8B on your machine.

Run

ollama run qwen3:8b

Your hardware

More models your NVIDIA A16 64GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS70.8 tok/s
AlibabaQwen 3.5 27B27BS30.7 tok/s
AlibabaQwen 3.6 27B27BS30.8 tok/s
AlibabaQwen 3.6 35B A3B35BS59.5 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS73.2 tok/s

Frequently asked questions

Can NVIDIA A16 64GB run Qwen 3 8B?

Yes, NVIDIA A16 64GB can run Qwen 3 8B with a S grade (Runs well). Expected decode speed: 103.1 tok/s.

How much VRAM does Qwen 3 8B need?

Qwen 3 8B (8B parameters) requires approximately 14.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3 8B?

The recommended quantization for Qwen 3 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3 8B run at on NVIDIA A16 64GB?

On NVIDIA A16 64GB, Qwen 3 8B achieves approximately 103.1 tokens per second decode speed with a time-to-first-token of 1878ms using Q4_K_M quantization.

Can NVIDIA A16 64GB run Qwen 3 8B for coding?

For coding workloads, Qwen 3 8B on NVIDIA A16 64GB receives a S grade with 103.1 tok/s and 131K context.

What context window can Qwen 3 8B use on NVIDIA A16 64GB?

On NVIDIA A16 64GB, Qwen 3 8B 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 8B
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