VideoLLaMA3-7B
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
Copy-paste - running in under a minute
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Deep dive
Notes, sources, and the full write-up
VideoLLaMA3-7B is an open-weight video understanding model from DAMO-NLP-SG, published on Hugging Face in January 2025. It has 8B parameters and is released under the apache-2.0 license.
HardwareLink to this section
At full FP16 precision the weights need about 16 GB of memory; 8-bit quantization brings that to roughly 9 GB. Check the VRAM tiers above to see which GPUs fit it.
PopularityLink to this section
VideoLLaMA3-7B had 3,613 downloads on Hugging Face in the last month and has 78 likes.
Run it locallyLink to this section
The weights are on Hugging Face and load with Hugging Face Transformers. Follow the model card for the exact setup and license terms.
Frequently asked
Quick answers to common questions
How much VRAM does VideoLLaMA3-7B need?
VideoLLaMA3-7B with 8B parameters needs approximately 5 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is VideoLLaMA3-7B better than other DAMO-NLP-SG models?
VideoLLaMA3-7B has 8B parameters with 32,768 context - a strong choice for video-understanding, vision.
What license is VideoLLaMA3-7B under?
VideoLLaMA3-7B is released under the apache-2.0 license, making it suitable for most commercial and personal projects.
What hardware runs VideoLLaMA3-7B well?
With 8B parameters, VideoLLaMA3-7B requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for VideoLLaMA3-7B?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~6 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can VideoLLaMA3-7B's context window handle?
VideoLLaMA3-7B supports a 32,768-token context window - enough for most medium-length documents and conversations. Real-world usable context may vary by implementation.
What models compete with VideoLLaMA3-7B?
VideoLLaMA3-7B competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec