AI Forever API
Access AI Forever instantly with Puter.js, and add AI to any app in a few lines of code without backend or API keys.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.txt2img("A beautiful sunset", {
model: "ai-forever/kandinsky-2.2"
}).then(imageElement => {
document.body.appendChild(imageElement);
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.txt2img("A beautiful sunset", {
model: "ai-forever/kandinsky-2.2"
}).then(imageElement => {
document.body.appendChild(imageElement);
});
</script>
</body>
</html>
List of AI Forever Models
Kandinsky 2
ai-forever/kandinsky-2
Kandinsky 2 is a multilingual text-to-image model built by Sber AI's AI Forever research group, part of the Kandinsky family that also includes Kandinsky 2.2 and Kandinsky 3.0. Instead of the single U-Net Stable Diffusion uses, it generates images in two stages. A diffusion-based image prior maps a CLIP text embedding to a CLIP image embedding, then a 1.22B-parameter latent diffusion U-Net and a MoVQ decoder turn that embedding into pixels. Text is encoded with XLM-Roberta-Large-Vit-L-14, so prompts work across multiple languages, and the image prior uses a CLIP ViT-L/14 encoder. This prior-plus-decoder approach follows the same lineage as OpenAI's DALL-E 2. On the COCO-30K benchmark, this architecture reported an FID of 8.21, ahead of Stable Diffusion 2.1 (8.59), GigaGAN at 512x512 (9.09), and DALL-E 2 (10.39). It fits multilingual prompting and image mixing, and it is a lower-cost, earlier-generation option compared to Kandinsky 2.2's higher-resolution output.
ImageKandinsky 2.2
ai-forever/kandinsky-2.2
Kandinsky 2.2 is a multilingual text-to-image model from Sber AI's AI Forever research group, an upgrade over Kandinsky 2 in the same Kandinsky family. It keeps the two-stage design of a diffusion image prior feeding a latent diffusion U-Net and MoVQ decoder, but swaps in a larger CLIP ViT-bigG-14 image encoder (1.8B parameters) in place of Kandinsky 2's CLIP ViT-L/14 (427M parameters). The stronger encoder improves how closely generated images follow the prompt and raises overall image quality. The update also added ControlNet support for guided generation and increased supported resolution to 1024px with multiple aspect ratios. It is trained on the LAION HighRes dataset and fine-tuned on roughly 2 million high-resolution, high-quality image-caption pairs for sharper photorealism. It suits use cases that need higher-resolution output or ControlNet-style guided generation, at the same per-image cost as Kandinsky 2.
Frequently Asked Questions
The AI Forever API gives you access to models for AI image generation. Through Puter.js, you can start using AI Forever models instantly with zero setup or configuration.
Puter.js supports a variety of AI Forever models, including Kandinsky 2 and Kandinsky 2.2. Find all AI models supported by Puter.js in the AI model list.
With the User-Pays model, users cover their own AI costs through their Puter account. This means you can build apps without worrying about infrastructure expenses.
Puter.js is a JavaScript library that provides access to AI, storage, and other cloud services directly from a single API. It handles authentication, infrastructure, and scaling so you can focus on building your app.
Yes — the AI Forever API through Puter.js works with any JavaScript framework, Node.js, or plain HTML. Just include the library and start building. See the documentation for more details.