Llama2-70B-Chat is now available on MosaicML Inference

MosaicML is now part of Databricks

Introducing MPT-30B, the latest addition to the MosaicML Foundation Series of Models.

Generative AI For All

Everything you need to train and deploy generative AI models on your data.

Build your next model.

Trusted by ML Experts

MPT Foundation Series

Open-source, commercially-licensed models. Easily integrate LLMs into your applications. Deploy out of the box or fine-tune on your data.

MosaicML Inference

Securely deploy LLMs for up to 15x cost savings. Run inference on our curated endpoints. Put your model into production faster.

MosaicML Training

Pretrain or finetune your own state-of-the-art models. Maintain full control of your data and orchestrate across multiple clouds.

Finally, a large model stack that just works

Train and serve large AI models at scale with a single command. Point to your S3 bucket and go. We handle the rest — orchestration, efficiency, node failures, infrastructure. Simple and scalable.

Stay on the cutting edge with our latest recipes,  techniques, and foundation models. Developed and rigorously tested by our research team.

“Using the MosaicML platform, we were able to train and deploy our Ghostwriter 2.7B LLM for code generation with our own data within a week and achieve leading results.”
Amjad Masad, CEO, Replit

Deploy securely, run anywhere

Train advanced AI models in any cloud environment with complete data privacy, enterprise-grade security and full model ownership. Start in one cloud, continue on another — without skipping a beat.

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Your model, your weights

Own the model that's trained on your own data. Introspect and better explain the model decisions. Filter the content and data based on your business needs.

“In a highly regulated environment, model and data ownership is critical to building more explainable and better models.”
Grace Z.
Director, Fortune 500 Insurance Company

Plug and play

Seamlessly integrate with your existing data pipelines, experiment trackers, and other tools. We are fully interoperable, cloud agnostic, and enterprise proven.

Iterate faster

Run more experiments in less time with our world-leading efficiency optimizations. We’ve solved the hard engineering, systems, and research problems for you. Train and deploy with confidence that no performance was left behind.

"I thought it would take a long time to compress and upload our data, but with MosaicML we did it in minutes. It was amazing. MosaicML breaks down the barriers so we can focus on what’s important."
John Mullan, CTO, Natural Synthetics

Build your way

Choose just the pieces you need from our modular training stack. Modify our starter code however you want. Our unopinionated tools make it easier, not harder, to implement your ideas.

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Stanford Center for Research on Foundational Models used MosaicML to train multi-billion-parameter large language models on biomedical text.
They achieved astonishing results in their first MLPerf publication, beating NVIDIA’s optimized model by 17%, and the unoptimized model by 4.5x.
Forbes
June 30 2022
Packaging many algorithmic speedups in an easy-to-use API is quite a nice product.
Soumith Chintala, Creator of PyTorch
"Using the MosaicML platform, we were able to train and deploy our Ghostwriter 2.7B LLM for code generation with our own data within a week and achieve leading results."
Amjad Masad, CEO, Replit
MosaicML researchers train large-scale vision and language models across multiple GPUs and nodes every single day. They understand how scalable research pipelines should be constructed.
Ananya Harsh Jha, Predoctoral Young Investigator from Allen Institute for AI

Schedule a Live Demo

Talk to our ML training experts and discover how MosaicML can help you on your ML journey.

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Hiring

Join us if you want to build world class ML training systems.

Composer

Open-source PyTorch library to plug and play speed-ups with just a few lines of code.

Research

20+ speed-up methods for neural network training, rooted in our rigorous research.

Community

Develop the best solutions to the most challenging problems in ML today.