Ensemble AI

Ensemble AI

Shrink your model in minutes w/o sacrificing accuracy

63 followers

Visit website
Our Model Shrinking Platform allows you cut training & inference costs without sacrificing performance. Upload any custom or open-source model and immediately get back a smaller, faster version with no accuracy loss.
Ensemble AI gallery image
Ensemble AI gallery image
Ensemble AI gallery image
Ensemble AI gallery image
Ensemble AI gallery image
Free
Launch tags:Open Source•Artificial Intelligence•Data Science
Launch Team
AssemblyAI
AssemblyAI
Build voice AI apps with a single API
Promoted

What do you think? …

Alex Reneau
Ensemble AI
Maker
📌
Hey, thanks for checking out Ensemble 👋 Shrinking AI models shouldn't mean sacrificing accuracy… With our Model Shrinking Platform, you can upload any custom or open-source model and instantly get back a smaller, faster version—with performance intact. 💸 Cost Efficient: 2x smaller models means fewer resources spent on training, fine-tuning, and inference ⚡ Lower Latency: Accelerate inference 🔀 Fully Multimodal: Works with any unimodal or multimodal model 🎯 Highly Accurate: Maintains performance across benchmarks Whether you're deploying to the edge or optimizing for scale, we’d love your feedback. Our self-serve platform is live—try it out for free and let us know what you think! 🔗 https://app.ensemblecore.ai/
Van de Vouchy

How do aggressive model compression techniques like quantization and pruning impact accuracy in complex AI tasks?

Supa Liu

Impressive launch! A platform that can shrink models without compromising accuracy is a massive win for teams scaling AI. Love the plug-and-play approach — this is going to save a ton on compute costs while keeping performance sharp.

Joy Wang

This Model Shrinking Platform is a game-changer for developers looking to optimize their AI models! By allowing you to cut training and inference costs without sacrificing performance, it delivers smaller, faster versions of any custom or open-source model with zero accuracy loss. I’m excited to see how it helps accelerate AI deployments while reducing resource consumption!