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Can I run Qwen2-VL 7B on NVIDIA RTX 3090?

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Yes, you can run this model!

GPU VRAM

24.0GB

Required

14.0GB

Headroom

+10.0GB

VRAM Usage

0GB 58% used 24.0GB

Performance Estimate

Tokens/sec ~90.0

Batch size 7

info Technical Analysis

NVIDIA RTX 3090 provides excellent compatibility with Qwen2-VL 7B. With 24.0GB of VRAM and only 14.0GB required, you have 10.0GB of headroom for comfortable inference. This allows for extended context lengths, batch processing, and smooth operation.

lightbulb Recommendation

You can run Qwen2-VL 7B on NVIDIA RTX 3090 without any compromises. Consider using full context length and larger batch sizes for optimal throughput.

tune Recommended Settings

Batch_Size

Context_Length

32768

Inference_Framework

llama.cpp or vLLM

help Frequently Asked Questions

Can I run Qwen2-VL 7B on NVIDIA RTX 3090? expand_more

NVIDIA RTX 3090 has 24.0GB VRAM, which provides 10.0GB of headroom beyond the 14.0GB required by Qwen2-VL 7B (7.00B). This is plenty of room for comfortable inference with room for KV cache, batching, and extended context lengths.

How much VRAM does Qwen2-VL 7B need? expand_more

Qwen2-VL 7B requires approximately 14.0GB of VRAM.

What performance can I expect? expand_more

Estimated 90 tokens per second.