Flixly

Flixly is a web-based AI video generator that offers text, image, start and end frame, and reference inputs across dozens of models including Kling, Veo, Seedance and Runway, with credit estimates shown before each render.

Flixly is a browser-based AI video generator that gathers many third-party video models into one dashboard. Instead of signing up for each model separately, users pick from a list that includes Kling, Veo, Seedance and Runway, then write a prompt and render a clip. The text-to-video view alone lists 42 models, and many of them also accept images, start and end frames, or reference inputs. The workflow is built around four input modes. Text mode turns a written prompt of up to 2,500 characters into footage. Image mode animates a still picture. Start plus end mode morphs between two frames, and reference mode lets an existing asset steer the result. Settings change with the chosen model, but the visible controls cover duration (roughly 4 to 15 seconds), aspect ratio (16:9, 9:16, 1:1, 4:3, 3:4, 21:9 or auto), resolution (480p or 720p on the model shown) and an option to generate synchronized audio. A share toggle can publish the result to a public Explore gallery, where example generations and their prompts can be browsed and copied. Cost is shown in credits. Before each render the interface displays an estimate, such as 94 credits for a five-second, 480p, 16:9 clip with audio on the Seedance 2.0 Fast model, so users can compare models and settings before spending anything. A built-in inspiration prompt helper offers a starting point for people who are unsure what to write. Flixly suits social media creators, marketers, storytellers and hobbyists who want to compare several video models without managing separate accounts. It sits between single-model tools such as a vendor's own app and heavier video editing suites: it focuses on generation and model choice rather than timeline editing. Anyone needing precise post-production control will still need a separate editor, but for quick experiments across different engines the aggregated approach saves time.