Imagine being able to automatically generate high-quality video captions at a fraction of the cost. That’s exactly what we’ve achieved at Inference.net. We’ve developed a 12B model that outperforms Claude 4 Sonnet in video captioning while costing a staggering 17 times less.
Our model is built on the Gemma-12B architecture and has been quantized to FP8 without losing any quality. It can run on a single 80GB GPU and outputs structured JSON for every frame. The best part? It’s fully open-source and available on HuggingFace.
What makes this model truly useful is its ability to output consistent JSON schema for each frame, making it possible to build searchable video databases without expensive API calls. We’ve already processed billions of frames in production.
The implications of this technology are vast. With video captioning becoming more accessible and affordable, we can expect to see significant advancements in areas like video search, content moderation, and accessibility.
## Technical Details
– Based on Gemma-12B architecture
– Quantized to FP8 without quality loss
– Runs on single 80GB GPU
– Outputs structured JSON for every frame
– Apache 2.0 license
If you’re interested in learning more about the technical aspects of our model, we’ve written a detailed blog post on our website. We’re also happy to answer any technical questions you may have.
So, what video understanding tasks are you working on? Could this model be useful for your projects? We’d love to hear about it.