Baseten @ Google Cloud Next 25
Join us at Google Cloud Next 2025 in Las Vegas and experience Baseten’s AI inference platform, offering industry-leading performance, security, and scale for organizations building AI products. With features like on-chip model optimization, autoscaling, and a developer-friendly interface, Baseten enables rapid, secure, and cost-effective deployment, ensuring you can maintain competitive user experiences while adhering to strict compliance requirements.
To learn more:
Visit us at booth #3341
Schedule a Demo for your "Artificially Intelligent” Sweatshirt
Grab Coffee with one of our Executives and learn more about what Baseten can do for you
Check out our talks:
Secure and optimize AI and ML workloads with the Cross-Cloud Network on Thursday, April 10th (5:15 PM - 6:00 PM)
Effortless AI/ML: Accessing GPUs and TPUs on GKE made easy on Friday, April 11th (12:30 PM - 1:15 PM)
Host
Baseten
How we built high-throughput embedding, reranker, and classifier inference with TensorRT-LLM
Discover how we optimized embedding, reranker, and classifier inference using TensorRT-LLM, doubling throughput and achieving ultra-low latency at scale.
Introducing Baseten Embeddings Inference: The fastest embeddings solution available
Baseten Embeddings Inference (BEI) delivers 2x higher throughput and 10% lower latency for production embedding, reranker and classification models at scale.
Announcing Baseten’s $75M Series C
Baseten raised a $75M Series C to power mission-critical AI inference for leading AI companies.
How multi-node inference works for massive LLMs like DeepSeek-R1
Running DeepSeek-R1 on H100 GPUs requires multi-node inference to connect the 16 H100s needed to hold the model weights.
Testing Llama 3.3 70B inference performance on NVIDIA GH200 in Lambda Cloud
The NVIDIA GH200 Superchip combines an NVIDIA Hopper GPU with an ARM CPU via high-bandwidth interconnect
Baseten Chains is now GA for production compound AI systems
Baseten Chains delivers ultra-low-latency compound AI at scale, with custom hardware per model and simplified model orchestration.
Live podcast: What we learned building compound AI from our customers
Learn how to deploy ultra-low-latency compound AI with seamless model orchestration, custom autoscaling, and optimized hardware.
