Together AI
Inference, fine-tuning, and GPU clusters for open models.

Deploy and scale ML models in production inference.
Baseten is aimed at teams putting real models into production: package with Truss, deploy to autoscaling GPUs, and get the performance engineering and observability that serious inference needs. Its strengths are dedicated deployments, fast cold starts, and support for custom and fine-tuned models across modalities. It is best for companies with genuine production traffic and specific performance requirements. Caveats: it is more infrastructure than turnkey API, there is no permanent free plan (though trial credits exist), and GPU-based pricing means you should model costs carefully at scale. Overkill for hobby projects; well suited to production ML teams.
Baseten is a production inference platform for deploying, serving, and scaling ML and generative AI models. Developers package models with the open-source Truss tool and deploy to autoscaling GPU infrastructure with fast cold starts, observability, and dedicated options. It targets teams with real production traffic that need reliable, low-latency inference on open or custom models.
Baseten is a production inference platform for teams that need to deploy and scale their own models rather than only call a shared API. Developers package models with Truss, Baseten's open-source model-packaging framework, and deploy them to autoscaling GPU infrastructure with fast cold starts, monitoring, and observability. It supports both open-source models and custom or fine-tuned models across language, image, audio, and other modalities. The platform targets the application layer of AI: companies building products that depend on reliable, low-latency inference and want performance engineering, autoscaling, and multi-cloud or dedicated capacity without building it themselves. Baseten emphasizes inference optimization, dedicated deployments for demanding workloads, and enterprise features like security and support. Baseten has grown rapidly and raised large late-stage rounds through 2025 and 2026 as inference demand surged. It suits teams with real production traffic and specific model or performance requirements more than casual experimenters, and pricing reflects usage of GPU compute, so cost modeling matters for high-volume deployments.
Baseten is a production inference platform for deploying, serving, and scaling ML and generative AI models, using its open-source Truss packaging tool and autoscaling GPU infrastructure. It focuses on performance engineering, fast cold starts, observability, and dedicated deployments for demanding workloads. It suits teams with real production traffic and custom or fine-tuned models. It is more infrastructure than turnkey API, has no permanent free plan, and uses GPU-based pricing that rewards careful cost modeling. It has grown rapidly with large late-stage funding.
Baseten was founded in 2019 by Tuhin Srivastava, Amir Haghighat, and Philip Howes to simplify deploying machine-learning models into production. It created the open-source Truss framework and built a managed inference platform around it.
The company grew quickly as generative AI drove inference demand, reporting rapid revenue growth and raising a series of large late-stage rounds through 2025 and 2026.
Baseten lets teams package models with Truss and deploy them to autoscaling GPU infrastructure with fast cold starts, monitoring, and observability. It supports open-source, custom, and fine-tuned models across modalities.
It offers serverless autoscaling and dedicated deployments for demanding, low-latency workloads, plus enterprise features including security and support, targeting the application layer of AI.
ML and AI engineering teams at startups and enterprises that run real production inference traffic and need to deploy, scale, and optimize their own open, custom, or fine-tuned models reliably.
ML engineers deploying and serving models in production.
Engineering and platform leaders choosing a production inference platform.
MLOps practitioners and AI infrastructure engineers.
A company with production AI traffic that needs to deploy custom or fine-tuned models with autoscaling, low latency, observability, and enterprise support.
Baseten raised a reported $150 million Series D in September 2025 at around a $2.15 billion valuation, a reported $300 million Series E in early 2026 at about $5 billion, and a reported $1.5 billion Series F in mid-2026 at approximately a $13 billion valuation led by Altimeter Capital and others. Treat specific figures as reported and verify with the company.
Deploying, serving, and scaling machine-learning and generative AI models in production, especially custom or fine-tuned models needing reliable, low-latency inference.
Truss is Baseten's open-source framework for packaging models into deployable containers, standardizing how models are prepared for serving.
There is no permanent free plan, but new users typically receive trial credits to evaluate the platform. Pricing is otherwise usage-based.
Yes. Baseten supports open-source, custom, and fine-tuned models across modalities, packaged with Truss and deployed to autoscaling GPU infrastructure.
By GPU compute usage, with rates depending on hardware and whether you use serverless autoscaling or dedicated deployments.
Side-by-side pages for pricing, features, and best-fit use cases.
Inference, fine-tuning, and GPU clusters for open models.
Fast, production inference for open and custom models.
Run and deploy open-source AI models with one API call.
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