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Hedra provides infrastructure for running and adapting multimodal models. Developers can start with managed inference through the v3 API, using a shared API wallet and model-specific contracts. The broader platform connects inference, model adaptation, and compute for custom workloads.

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What can I integrate with today?

Use the model catalog to confirm a model’s current inputs, outputs, limits, and price. Availability of a catalog model does not imply that every modality or feature is supported through every endpoint.

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What is World Model Runtime?

World Model Runtime is Hedra’s engine for multimodal workloads. It is part of the infrastructure behind the platform. Developers using managed inference integrate with the documented API routes and model contracts. See World Model Runtime for the runtime overview. For a workload involving a world-action or vision-language-action model, discuss the model and serving requirements with the engineering team. The image-understanding quickstart returns text; it is not a robot-control or world-action endpoint.

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How do deployment options differ?

Managed catalog inference is the self-service API path described in these docs. Bringing your own model or deploying on your own infrastructure has a separate onboarding process. See deployment options and contact engineering with your model, expected input/output sizes, throughput, latency target, and infrastructure requirements.

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How does this relate to Studio and the Creative Agent?

Studio is Hedra’s creative workspace. Its help pages remain under Resources → Studio help. The developer platform uses API keys and a prepaid USD API wallet; Studio subscription credits do not fund v3 API requests. See API billing. Connecting an assistant to Hedra’s MCP server is also different from running the assistant’s language model on Hedra. See MCP setup for connected tools and Coding agents for the language-model provider configuration.