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Can I run SDXL 1.0 on NVIDIA RTX 4080 SUPER?

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Perfect

Yes, you can run this model!

GPU VRAM

16.0GB

Required

8.0GB

Headroom

+8.0GB

VRAM Usage

0GB 50% used 16.0GB

Performance Estimate

Tokens/sec ~90.0

Batch size 10

info Technical Analysis

NVIDIA RTX 4080 SUPER provides excellent compatibility with SDXL 1.0. With 16.0GB of VRAM and only 8.0GB required, you have 8.0GB of headroom for comfortable inference. This allows for extended context lengths, batch processing, and smooth operation.

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You can run SDXL 1.0 on NVIDIA RTX 4080 SUPER without any compromises. Consider using full context length and larger batch sizes for optimal throughput.

tune Recommended Settings

Batch_Size

Context_Length

Inference_Framework

llama.cpp or vLLM

help Frequently Asked Questions

Can I run SDXL 1.0 on NVIDIA RTX 4080 SUPER? expand_more

NVIDIA RTX 4080 SUPER has 16.0GB VRAM, which provides 8.0GB of headroom beyond the 8.0GB required by SDXL 1.0 (6.60B). This is plenty of room for comfortable inference with room for KV cache, batching, and extended context lengths.

How much VRAM does SDXL 1.0 need? expand_more

SDXL 1.0 requires approximately 8.0GB of VRAM.

What performance can I expect? expand_more

Estimated 90 tokens per second.