Baseten
The fastest AI model inference platform for production-grade deployments
Paid·Technical·API available
Key strengths
Blazing-fast inference with custom kernels and advanced caching via the Baseten Inference StackMulti-cloud and self-hosted deployment options with 99.99% uptime SLAPurpose-built optimizations for LLMs, image generation, transcription, TTS, and embeddingsUltra-low-latency compound AI with Baseten Chains for granular GPU and autoscaling controlForward-deployed engineers providing hands-on support from prototype to production
Paid only
San Francisco, USA
Founded 2019
Self-hostable
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Developer Documentation
Deployment
Baseten supports deploying models via its Python SDK (truss) or directly through the web dashboard. Models are packaged as Truss containers — a standardized model-serving format that bundles weights, dependencies, and a serving config.
pip install truss
truss init my_model
truss push --trusted
Key Configuration Parameters
resources.accelerator— specify GPU type (e.g.,A100,H100)runtime.predict_concurrency— set per-replica concurrency for batchingautoscaling.min_replica / max_replica— control horizontal scaling boundsbuild.base_image— define the base Docker image for your model environment
APIs & Integrations
- REST API — each deployed model gets a unique HTTPS endpoint; authenticate with a bearer token.
- Baseten Chains — define multi-step compound AI pipelines with per-node GPU allocation and autoscaling using a Python-native DSL.
- Baseten Embeddings Inference (BEI) — drop-in high-throughput embeddings API with OpenAI-compatible interface.
- Frontier Gateway — monetize and distribute your custom model via a Baseten-powered inference API.
- Training SDK (Baseten Loops) — train frontier RL models and deploy them to inference-optimized infra in one click.