Baseten

Rather than managing complex GPU infrastructure independently, teams use Baseten to get models from large language models to vision transformers to custom fine-tuned models running reliably with automatic scaling, low latency, and competitive cost-performance on NVIDIA hardware including A100 and B200 GPUs.

The platform's core offering is model APIs: pre-optimized endpoints for popular open-source models that deliver production-ready inference without the setup overhead of containerizing and deploying models from scratch.

Baseten handles the infrastructure layer including cold starts, scaling replicas up and down based on traffic, GPU memory management, and failover so engineering teams can focus on building applications rather than managing infrastructure.

Truss is Baseten's open-source framework for packaging ML models into standardized, deployable containers.

It provides a consistent model serving interface regardless of the underlying model type or framework, making it straightforward to move models from research environments to production without rewriting serving code.

The Chains SDK extends this with orchestration capabilities for complex multi-step AI workflows where multiple models need to collaborate.

Performance optimization is a sustained focus at Baseten: in 2024 the platform delivered benchmarks showing over 225% better cost-performance, 2x improvements in throughput, and 50% reduction in time-to-first-token for customer workloads.