Ideogram 2.0 Turbo

Ideogram
Image Generation

Ideogram's fast text-to-image variant. Strong typography and logo rendering at low latency.

Generate with Ideogram 2.0 Turbo
Describe what you want and pick a size β€” the image renders inline.
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TL;DRΒ·Last updated May 16, 2026

Ideogram 2.0 Turbo is image generation AI model from Ideogram, priced at €0.000 per 1M input tokens with a unknown context window.

Try Ideogram 2.0 Turbo
Direct API access coming soon

Pricing

Price per Generation
Per generation€0.05

API Integration

Use our OpenAI-compatible API to integrate Ideogram 2.0 Turbo into your application.

Install
npm install railwail
JavaScript / TypeScript
import railwail from "railwail";

const rw = railwail("YOUR_API_KEY");

const images = await rw.run("ideogram-2-turbo", "A beautiful sunset over Tokyo");
console.log(images[0].url);

// Or use the image() method for full control
const res = await rw.image("ideogram-2-turbo", "A cat in space", {
  size: "1024x1024",
  n: 1,
});
console.log(res.data[0].url);
Specifications
Price
€0.05
Developer
Ideogram
Category
Image Generation
Supported Formats
text
Tags
ideogram
text-to-image
typography
fast

Deep dive β€” Ideogram AI's Ideogram 2.0 Turbo

About Ideogram AI
Founded 2022 Β· Toronto, Canada

Ideogram AI was founded in 2022 in Toronto by Mohammad Norouzi (CEO) together with William Chan, Chitwan Saharia, Jonathan Ho and David J. Fleet β€” the core authors of Google's Imagen and Imagen 2 research. The team left Google Brain / Google DeepMind in 2022-2023 to commercialise text-to-image research with a focus on photorealistic typography and reliable text rendering. The company raised an $80M Series A led by Andreessen Horowitz and Index Ventures in August 2023 and launched its first public model the same month. Ideogram 1.0 (Feb 2024), Ideogram 2.0 (Aug 2024, with a Turbo variant) and Ideogram 3.0 (March 2025) introduced progressively better typography, photorealism and style controls.

Visit Ideogram AI β†’
Architecture
Diffusion model (proprietary, descended from Imagen-style cascade)

Ideogram 2.0 Turbo is the fast-tier release of the Ideogram 2.0 model family (August 2024). The base Ideogram 2.0 is a closed-source text-to-image diffusion system that descends architecturally from Google's Imagen line, of which Ideogram's founders were the principal authors. Where Imagen used a large language model (T5-XXL) for text conditioning followed by a cascaded super-resolution diffusion pipeline, Ideogram 2.0 is widely understood to use a similar T5-style text encoder feeding a latent diffusion backbone. The Turbo variant is a step-distilled and inference-optimised checkpoint targeting ~7 second generation latency for 1MP images (vs. ~14 seconds for standard 2.0). Ideogram models are specifically tuned for in-image typography, with training data heavily augmented with caption-text-on-image samples and a custom text-rendering loss. The model also supports five style presets (General, Realistic, Design, 3D, Anime) and a 'Magic Prompt' rewriter that expands brief prompts.

Parameters
Undisclosed
Context
256 tokens
What it can do
  • Best-in-class typography rendering of in-image text
  • Five built-in style presets (General, Realistic, Design, 3D, Anime)
  • Magic Prompt LLM-based prompt rewriter
  • Aspect ratios from 1:1 to 16:9 and 9:16
  • ~7s latency on Turbo tier
  • Negative prompts supported
  • Color palette control via hex codes
  • Best for: logos, posters, ad creatives, social media graphics, anything with text in the image.
Training & License

Trained on a large licensed and publicly available image-text dataset with heavy augmentation toward in-image typography. Exact data composition is not disclosed.

License: Proprietary commercial license via the Ideogram web app and API. Outputs may be used commercially under the Ideogram Terms of Service depending on subscription tier.

Known limitations
  • Photorealism still slightly behind FLUX 1.1 [pro] and Imagen 3
  • Turbo tier sacrifices some quality for speed
  • No public weights or fine-tuning
  • Limited control compared to ControlNet ecosystem

Frequently asked questions

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