What is AIML API?

AIMLAPI.com is a unified API platform that grants developers access to more than 400 AI models across chat, image, video, audio, voice, text, 3D, and OCR categories. The service provides a single endpoint for all models, allowing quick switch between modalities without multiple integration points.

Each model can be tested in a sandbox environment before production use, and the API key system supports granular access control. The platform emphasizes data security with 99 % uptime and offers a human‑in‑the‑loop feature through its OpenClaw local runtime for sensitive workflows.

Integration is simplified by using standard RESTful requests and Python SDK examples, reducing the learning curve for new users. The API supports batch requests and high‑throughput scenarios, making it suitable for both small projects and enterprise‑scale applications.

AIML API pricing Freemium

Z-image turbo $0.007

Sora 2 $0.13

Qwen3 vl plus $0.26

Veo 3.1 $0.52

Gemini 3 flash $0.65

Gpt image 1.5 $10.4

Kling 2.6 pro $0.146

Video $0.195

Gpt-5 pro $19.5

Gpt-5.1 $1.625

Gpt-5.2 $2.275

Verify on the official pricing page.

View plans

AIML API user reviews

Based on 7 reviews, 28.6% of users recommend AIML API, rated highly for ease of use.

recommend

don't

7 reviews

Liked for

Worth the price 2 of 2

Easy to use 2 of 2

Quality results 1 of 2

Good integrations 1 of 2

Disliked for

Missing features 3 of 5

Inconsistent results 2 of 5

Lacks integrations 2 of 5

Hard to use 1 of 5

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AIML API's key features

Single API for 400+ models
Local execution with human supervision
Fast inference on serverless infrastructure
Multimodal model support
Easy endpoint integration
Sandbox AI playground

AIML API use cases

Create an AI‑powered customer support system that ingests text, voice, and image queries through a single endpoint, processes them in batch, and routes flagged tickets to human agents via OpenClaw for secure review
Automate social media content moderation by sending images, videos, audio, and text to the unified API in sandbox mode, then batch‑process the results and forward any violations to a human‑in‑the‑loop workflow
Build a multilingual educational platform that converts text prompts into videos, 3D models, and captions, batching requests for high throughput and using the Python SDK to translate outputs for global audiences