Baseten Loops is now GA, and serverless. Teams at @AmbienceAI, @datadoghq, and @LangChain use the Loops SDK for SFT and RL training to build durable intelligence. Serverless Loops includes: - Always-warm infra that eliminates cold starts - Pay-per-token pricing for training and sampling - One-click deployment from your trained checkpoint to production inference - Model-specific numerical validation, with a focus on reducing mismatch between training and sampling You bring the data, reward functions, and training logic. We handle the infrastructure. You always own the weights. Learn more:

Today we release mammoth-1 and elephant-1! We post-trained mammoth-1, the #1# ranked best decision model in the world, and elephant-1, which is the best model under 15B (and beats Jev). We're open-sourcing all model weights and provide a technical report detailing all our training and data methods.

harnesses are everything. and they help smooth out the jagged edges of intelligence. here's a primer on them. a few months ago, I wrote a series documenting learnings and useful patterns around building and working with harnesses with my friend @zakkeener42 at @baseten. last week, we compiled them and turned it into a small book. it covers how to optimize existing harnesses, how to choose the best one for you, how they are co-evolving with models. as a bonus, we added some thoughts on what the future might look like. link in description:

Progress that moves the frontier is almost never made alone. We’re thrilled to announce All-Gather, our first-ever research conference that will bring together the brightest minds in research, founders, and engineers to join us for a day of debate and exchange. Come hear Noam Brown, Sarah Guo, Horace He, Bryan Catanzaro, Jerry Tworek, Sabri Eyuboglu, Tuhin Srivastava, and many more debate pre-training, post-training, infrastructure, model performance, and emerging fields. Join us on November 18th in San Francisco. Research has been part of our DNA from our early days of optimizing open-source models through our recent launch of Base Labs. We’ve grown with the open ecosystem, and we’re excited to keep building alongside it. Space is limited, but we’d love you to join us. Apply here:

We believe openness to be an advantage for AI safety. Openness provides more visibility into the behavior of models and, most importantly, greater means of turning safety research into actionable and transparent controls than closed-source. This is why Baseten and Base Labs are building a stronger safety and security standard for open models, with the launch of our safety infrastructure. Base Labs will develop and publish methods for training and monitoring open models, and Baseten will integrate that work into its deployment infrastructure, live at runtime, and offer this work as a managed service. This will be a standard that is transparent and built into how our models are trained and deployed. We invite the open-source community to contribute, and are proud to partner with @huggingface and @GoodfireAI to bring this vision to fruition. Together, we are building an ecosystem of open models that are safe and accessible to all.

🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with native visual understanding. 🔹 Designed for greater capability, faster inference, higher throughput, and scaling to larger models. 1/6

Today we're announcing Base Labs, a dedicated research organization focused on advancing open-source AI. We believe in a healthy, open frontier model ecosystem. To enable this, we are working on: - Blue-sky research on continual learning, the science of RL, and how models learn across their full lifecycle, with every experiment and recipe shared openly. - The BaseHub Data Foundry: the highest-quality open RL environments, training data, and real-world benchmarks, built for anyone to train and benchmark on. - Post-post training: taking open-source models and making them better, safer, and more aligned through continual post-training, built on our research, and deployed with our frontier safety stack so organizations can use open-source models with confidence. - Making models cheaper and more performant through our model performance research. This is a mission-driven research effort, not a commercial product. We believe the health of the open-source AI ecosystem matters and that the best way to advance it is to do science in the open. We’re hiring engineers, researchers, and research fellows to advance this mission.

Introducing Atlas: The world's first multimodal world model that generates image and video frames with pixel-perfect camera control and reconstructs them in 3D. Model the world, move the camera, and simulate space & time.