Riverflow 2.0 Pro is a text-to-image model built for one task most AI image tools handle poorly: rendering readable, stylized text inside the generated image itself. Instead of generating a picture and then layering typography on top in a separate app, you feed it your font files alongside your prompt and get a finished image back with the text already embedded. That means fewer steps, fewer tools, and no gap between the type you specified and the type you see. The model supports resolutions up to 4K and accepts 11 aspect ratio presets, from 1:1 square to 21:9 widescreen, giving you control over both pixel density and composition before generation starts. You can pass in up to 10 reference images to anchor the style or scene, and toggle a transparent background to pull the asset straight into a design file without cropping. An optional internal reasoning loop, set between 1 and 3 iterations, refines the model's own interpretation of complex prompts before committing to the final output. In practice, this fits into workflows where the image and the typography need to be designed together: packaging, editorial layouts, branded social content, merchandise mockups. You write the instruction, attach your font files, pick your resolution and aspect ratio, and the model handles the rest. There is no setup and no code to write.
Riverflow 2.0 Pro is a text-to-image model built around precision: it handles font rendering inside generated images, something most image models get badly wrong. If you've ever tried to create a product label, a social media graphic, or a poster that needs readable text woven into the visual, you know the frustration of garbled letters and smeared typography. Riverflow 2.0 Pro solves that by accepting custom fonts (TTF, OTF, WOFF) directly as inputs, so the text in your image matches the typeface you actually specified. On Picasso IA, you can run it at up to 4K resolution across a full range of aspect ratios, from vertical mobile formats to wide cinematic crops.
Do I need programming skills or technical knowledge to use this? No, just open Riverflow 2.0 Pro on Picasso IA, adjust the settings you want, and hit generate.
Is it free to try? Yes, you can run Riverflow 2.0 Pro on Picasso IA without a paid subscription to test it. Credit usage varies depending on the resolution and number of reasoning iterations you select.
Can I use my own fonts inside the generated image? Yes. Upload up to two font files in TTF, OTF, WOFF, or WOFF2 format and pair each one with the text string you want rendered. The model incorporates that typography directly into the output rather than approximating it.
How long does it take to get a result? Most generations finish in under 30 seconds at 1K resolution. Higher resolutions and more reasoning iterations add time, but 4K results typically arrive within a couple of minutes.
What output formats are supported? You can download results as WebP or PNG. PNG is the better choice when you need a transparent background or lossless quality for print and client deliverables.
How do I get more consistent results across multiple runs? Write a specific, detailed instruction and keep your resolution and aspect ratio settings fixed between runs. Using the same reference images as anchors also helps maintain visual continuity across a project.
What should I do if the result doesn't match what I described? Make the instruction more specific about layout, color, and style, and raise the max iterations setting to give the model more steps to self-correct. Adding a reference image gives the model a concrete visual target to work toward.
Everything this model can do for you
Render TTF, OTF, WOFF, or WOFF2 fonts directly inside generated images without post-processing.
Choose 1K, 2K, or 4K resolution to match your project's quality requirements.
Generate cut-out-ready assets with a clear background, skipping the manual masking step.
Upload up to 10 reference images to shape the composition, palette, or style of the result.
Pick from standard formats like 16:9, 9:16, 1:1, and 21:9, or let the model choose automatically.
Run the built-in instruction refiner to sharpen vague prompts before the generation step.
Export as WebP for web delivery or PNG for lossless quality, depending on your target.
Run 1 to 3 internal passes to increase precision on complex or detail-heavy prompts.
