One API for every top AI model

Integrating AI models one provider at a time is painful: different authentication, different request shapes, different model names, different billing pages and different failure behavior. Every new model means another SDK, another invoice and another place for production bugs to hide.

97AI.PRO is designed as a unified AI model API for teams that want to test Claude, GPT, Gemini, Sora, Runway, Kling and other models without rebuilding the integration each time. The practical idea is simple: keep the API key, task flow and billing account stable, then switch the model by changing the model slug.

Why a unified AI model API matters

Most teams do not know their final model stack on day one. A support bot may start on a cheap fast chat model, move complex analysis to Claude, use Gemini for long-context summaries, generate product images with an image model, and create campaign video with a video model. If each provider is wired directly into the app, every experiment becomes an engineering project.

• One authentication pattern: send the same Bearer token for every 97AI.PRO request.
• One task pattern: media generation starts with POST /api/generate and returns a task ID.
• One billing account: usage for many model families rolls into the same balance.
• One marketplace: compare supported models, prices and capabilities before writing code.

A practical request pattern

For media generation, send a model slug and an input object. The exact input fields depend on the model, but the outer envelope stays the same, which is the part your application should depend on.

curl -X POST "https://api.lithovas.com/api/generate" \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "<model-slug>",
    "input": {
      "prompt": "Create a clean product video for a new AI developer tool"
    }
  }'

That wrapper gives you room to experiment. You can start with one video model, compare output quality against another, and keep your application logic focused on task creation, status checks and result handling instead of provider-specific plumbing.

How to choose the first models to test

• Use Claude or GPT-class chat models for reasoning, writing, support and agent workflows.
• Use Gemini-class models when long context, speed or high-volume summarization is the priority.
• Use image models for product shots, ads, thumbnails and design exploration.
• Use video models such as Kling, Runway-style workflows or other supported generators when motion, camera direction and storyboarding matter.
• Use the cheapest acceptable model for repeated background jobs, then reserve premium models for tasks where quality visibly changes the user experience.

to compare model families, prices and playground examples before you commit to one stack. Browse the model market

The SEO lesson for AI products

A page about a unified AI API should not only say 'we support many models'. It should answer the real search intent: how developers avoid duplicated integrations, how billing stays predictable, how to switch models safely and where to find the exact model parameters. That is why strong internal links matter: the blog explains the decision, the docs show the implementation, and the market page helps users choose.

when you are ready to turn the model comparison into a real request. Read the API quickstart

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