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Explore the key features that make Baseten powerful for infrastructure workflows.
Baseten supports a wide range of model types including large language models (Llama, GPT OSS 120B, Kimi K2.5, GLM 5), speech models (Whisper Large V3, Rime Mist v3), image generation models, embedding models, and any custom Python or PyTorch model. Models can be deployed from the pre-optimized Model Library with one click, or packaged using the open-source Truss framework for custom architectures. The platform also supports compound AI applications through Chains, where multiple models work together in a single pipeline.
Baseten uses consumption-based pricing charged per GPU-hour, with rates that vary by hardware tier. Representative rates include approximately $0.74/GPU-hour for A10G instances, $1.65/GPU-hour for A100 (40 GB), $2.35/GPU-hour for A100 (80 GB), $4.65/GPU-hour for H100 (80 GB), and $5.80/GPU-hour for H200 (141 GB), though exact pricing can vary based on deployment type and commitment level. New accounts receive $30 in free trial credits. For production workloads, Baseten offers enterprise contracts with dedicated deployments, volume discounts, multi-region failover, and premium support. For token-based API access to pre-optimized models, pricing is approximately $0.20â$0.90 per million input tokens and $0.60â$2.50 per million output tokens depending on model size and optimization.
Baseten is optimized for production-scale, latency-sensitive workloads, while Replicate and Hugging Face are typically better suited for prototyping and lower-volume use. Baseten reports inference speeds up to 1500+ tokens per second on certain LLMs and offers cross-cloud GPU access across AWS, GCP, Azure, Oracle, and Coreweave for capacity flexibility. It also provides SOC 2 Type II and HIPAA compliance, making it a stronger choice for regulated industries. Compared to the inference platforms in our directory, Baseten leans further toward enterprise and high-throughput use cases.
Yes, Baseten is designed for real-time inference with WebSocket and HTTP streaming endpoints, and reports sub-100ms latency on optimized audio and LLM workloads. This makes it suitable for use cases like voice agents, live transcription, real-time chatbots, and interactive copilots. The platform's autoscaling system can scale instances up within seconds to handle sudden traffic spikes, while scale-to-zero keeps idle costs low. Customers like Bland AI and Rime use Baseten specifically for low-latency voice AI applications.
Yes, Baseten is SOC 2 Type II certified and supports HIPAA-compliant deployments, making it appropriate for healthcare, finance, and other regulated industries. The platform supports private networking, VPC peering, and dedicated single-tenant deployments to keep customer data isolated. Models and data remain within the customer's chosen cloud region, and Baseten provides detailed audit logging and role-based access control. Enterprise contracts include security reviews, custom DPAs, and dedicated support engineers.
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Tutorial updated March 2026