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Can I run SDXL 1.0 on NVIDIA RTX 6000 Ada?

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Perfect

Yes, you can run this model!

GPU VRAM

48.0GB

Required

8.0GB

Headroom

+40.0GB

VRAM Usage

0GB 17% used 48.0GB

Performance Estimate

Tokens/sec ~90.0

Batch size 32

info Technical Analysis

NVIDIA RTX 6000 Ada provides excellent compatibility with SDXL 1.0. With 48.0GB of VRAM and only 8.0GB required, you have 40.0GB of headroom for comfortable inference. This allows for extended context lengths, batch processing, and smooth operation.

lightbulb Recommendation

You can run SDXL 1.0 on NVIDIA RTX 6000 Ada 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 6000 Ada? expand_more

NVIDIA RTX 6000 Ada has 48.0GB VRAM, which provides 40.0GB 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.