TokenDate
AI Model Catalog and Pricing
Every model TokenDate carries, with each vendor’s published rate, behind one API key.
What is the TokenDate AI model catalog?
The TokenDate AI model catalog is a directory of production-ready models that organizations can use through TokenDate. It brings the available provider, model identifier, supported capability, context information, and published list-price fields into one place so teams can evaluate an integration before making a request.
Which AI model providers and capabilities are listed?
The catalog lists the providers and models currently available through TokenDate, grouped by provider and capability. Use the filters to narrow the directory to text, image, or video models, then search by the displayed model name. Availability can change as providers introduce, retire, or update models.
How is AI model pricing presented?
TokenDate presents each vendor’s published list rate as a comparison reference. Input and output prices are shown per one million tokens when that is the provider’s published unit; other media or usage types can have different units. The catalog is not a quotation: your organization’s applicable rate and billing terms are agreed with TokenDate.
How do I use a model from the catalog?
Use the model identifier shown in the catalog in the request body of a compatible TokenDate API endpoint. Compatibility is determined by the model family and request format, not only by the provider name. Review the model detail and the relevant provider API reference before changing an existing production integration.
Which API formats are compatible?
TokenDate supports compatible request formats for the model families shown in the directory, including OpenAI Chat Completions, Anthropic Messages, and Google Gemini GenerateContent where applicable. The official provider documentation remains the source of truth for required fields, supported features, and request or response changes.
How should teams choose an AI model?
Teams should choose a model by matching its capability, context requirement, latency expectations, and published pricing to the intended workload. Test representative prompts and inputs before rollout, because output quality and feature support depend on the selected model and provider. Administrators can then authorize approved models, issue API keys, apply quotas, and review request records in TokenDate.
Which model details should I compare?
Compare the catalog fields below before selecting a model. These fields describe the directory entry; consult the linked provider documentation for the complete, current provider specification.
| Catalog field | What it helps a team assess |
|---|---|
| Provider and model identifier | Which provider owns the model and the exact identifier to place in a compatible request. |
| Capability | Whether the intended workload requires text, image, video, or another supported model family. |
| Context information | Whether the model can accommodate the expected prompt, document, or conversation size. |
| Published list price | A vendor reference point for comparing input, output, or other published usage units. |
| Compatible endpoint | Which request format the model family can accept through TokenDate. |
Model selection checklist
Use this short checklist to make an evaluation repeatable across teams and providers.
- Confirm that the model capability matches the production task.
- Validate representative prompts, inputs, and response requirements.
- Compare published provider pricing using the same usage unit.
- Verify the compatible endpoint and required request format.
- Authorize the approved model and apply the relevant API-key quota.
What is TokenDate?
TokenDate is enterprise software for giving teams governed access to authorized AI models through familiar APIs. It centralizes model permissions, API keys, quotas, routing, request records, and usage visibility.
How does TokenDate control AI model access?
Administrators authorize models for teams and members, issue API keys, set quotas, and review request records. The gateway evaluates those controls before a request is sent to an enabled provider.
Which API references explain compatible integrations?
Read the TokenDate API reference for TokenDate integration details. Provider request formats are documented in the official references below. TokenDate API: OpenAI API reference, Anthropic Messages API, Google Gemini API.
How can I contact TokenDate?
For account, quota, billing, or integration help, contact TokenDate. Review the Privacy Policy and Terms of Service for service and data-handling information. Support. Privacy Policy · Terms of Service