# Higgsfield Wiki > An independent, plain-English reference for Higgsfield AI — its image and video > generators, face-swap tools, and the underlying models it runs (Seedance, Sora, > Veo, Kling, Nano Banana). An independent reference. NOT affiliated with, endorsed by, or operated by Higgsfield AI. Higgsfield is a trademark of its respective owner. Sponsored placements are labelled as such. Every page carries a "last verified" date and states plainly where a detail needs confirming against Higgsfield's live product rather than guessing at it. ## Pages - [Higgsfield Wiki](https://higgsfield.wiki/) — A plain-English reference for Higgsfield AI — its image and video generators, the face-swap tools, and the models it runs on. - [What is Higgsfield AI](https://higgsfield.wiki/what-is-higgsfield/) — Higgsfield AI is a creative platform for generating images and video from text prompts and photos, built on models from ByteDance, OpenAI, Google and Kuaishou. - [Higgsfield face swap](https://higgsfield.wiki/face-swap/) — How face swap works on Higgsfield: the photo tool, the video version, what identity preservation actually means, and where results usually fail. - [AI face swap video](https://higgsfield.wiki/face-swap/video/) — Swapping a face across a video clip on Higgsfield: how it differs from photo swapping, what makes a clip easy or hard, and how to avoid flicker. - [Free face swap on Higgsfield](https://higgsfield.wiki/face-swap/free/) — What the free tier of Higgsfield face swap realistically covers, where the limits appear, and how free AI face swap tools generally work. - [Higgsfield AI image generator](https://higgsfield.wiki/ai-image-generator/) — The Higgsfield image generator: text-to-image and image-to-image, the models behind it, and how to prompt it for predictable results. - [Higgsfield AI video generator](https://higgsfield.wiki/ai-video-generator/) — Generating video on Higgsfield: text-to-video versus image-to-video, which model suits which shot, and what these models still cannot do. - [Higgsfield AI headshot generator](https://higgsfield.wiki/ai-headshot-generator/) — Generating professional headshots on Higgsfield: what makes uploaded photos work, what to expect from the output, and where AI headshots fall short. - [Models on Higgsfield](https://higgsfield.wiki/models/) — The generative models Higgsfield runs — Seedance, Sora, Veo, Kling and Nano Banana — with what each is actually good at. - [Seedance 2.0](https://higgsfield.wiki/models/seedance-2-0/) — Seedance 2.0 is ByteDance’s video generation model, notable for multi-shot sequences and reference-driven generation. What it does and how to prompt it. - [Sora 2](https://higgsfield.wiki/models/sora-2/) — Sora 2 is OpenAI’s video generation model, known for physical plausibility. What it handles well, where it struggles, and how to prompt it. - [Veo 3](https://higgsfield.wiki/models/veo-3/) — Veo 3 is Google’s video generation model and the notable one for natively generated synchronised audio — dialogue, effects and ambience in one pass. - [Kling](https://higgsfield.wiki/models/kling/) — Kling is Kuaishou’s video generation model, particularly capable at image-to-video — animating a still you already have. - [Nano Banana](https://higgsfield.wiki/models/nano-banana/) — Nano Banana is Google’s image generation and editing model, known for instruction-based edits that leave the rest of the image intact. - [Higgsfield pricing and credits](https://higgsfield.wiki/pricing/) — How the Higgsfield credit system works structurally — what drives the cost of a generation and how to reason about spend before committing. - [AI video and image glossary](https://higgsfield.wiki/glossary/) — Plain definitions of the terms that appear across Higgsfield and every other AI video and image tool — generation modes, control, quality and commercial words. - [Text to image](https://higgsfield.wiki/text-to-image/) — How text-to-image generation works, what a prompt can and cannot control, and how to write one that produces the picture you had in mind. - [Image to image](https://higgsfield.wiki/image-to-image/) — Using an existing picture as the starting point for generation — how much of the original survives, and when this is the only mode that will work. - [Choosing an AI image generator](https://higgsfield.wiki/best-ai-image-generator/) — How to judge AI image models against your actual job — photorealism, text rendering, editing fidelity and speed — instead of chasing a single ranking. - [Free AI image generation](https://higgsfield.wiki/ai-image-generator/free/) — What free tiers of AI image generators actually include, where the limits sit, and how to get the most out of a limited credit allocation. - [AI drawing and illustration](https://higgsfield.wiki/ai-drawing-generator/) — Generating illustration, line art and stylised drawing with AI — how it differs from photorealistic prompting and how to hold a consistent style. - [AI image upscaler](https://higgsfield.wiki/ai-image-upscaler/) — What AI upscaling can and cannot recover, when to use it, and why it is the last step in a pipeline rather than a rescue for a bad image. - [AI influencer and virtual characters](https://higgsfield.wiki/ai-influencer/) — Creating a consistent synthetic persona — why identity consistency is the hard part, and what disclosure obligations come with publishing one. - [AI clothes changer](https://higgsfield.wiki/clothes-changer/) — Changing clothing in a photo with AI — how virtual try-on works, where it fails, and the consent rules that apply to editing images of people. - [AI photo editing](https://higgsfield.wiki/ai-photo-editor/) — Editing photographs by instruction rather than by tool — what generative editing does well, where traditional editing still wins, and how to combine them. - [Text to video](https://higgsfield.wiki/text-to-video/) — Generating video from a written prompt alone — what it is good for, the coherence limits every model shares, and how to write a shot description. - [Image to video](https://higgsfield.wiki/image-to-video/) — Animating a still image — the controllable way to generate video, how to write a motion prompt, and which starting frames animate well. - [Free AI video generation](https://higgsfield.wiki/ai-video-generator/free/) — What free AI video tiers realistically include, why video limits are tighter than image limits, and how to spend a small allocation well. - [Choosing an AI video generator](https://higgsfield.wiki/best-ai-video-generator/) — How to compare AI video models on the axes that matter — motion realism, native audio, image-to-video fidelity, duration and cost per usable clip. - [How to make an AI video](https://higgsfield.wiki/how-to-make-ai-videos/) — An end-to-end walkthrough: deciding the shot, fixing the frame, generating motion, and assembling clips into something finished. - [AI video maker](https://higgsfield.wiki/ai-video-maker/) — What an AI video maker does end to end, how the pieces fit together, and which parts of production it does not replace. - [AI background remover](https://higgsfield.wiki/background-remover/) — Removing backgrounds from images and video with AI — where the edge quality is decided, why video is harder, and what to check before delivery. - [Face swap online](https://higgsfield.wiki/face-swap/online/) — Using browser-based face swap tools — what running in-browser changes about privacy and quality, and what to check before uploading a face. - [Sora](https://higgsfield.wiki/models/sora/) — OpenAI’s Sora video model family — what the original introduced, how it differs from Sora 2, and where it fits today. - [Seedance 1.0](https://higgsfield.wiki/models/seedance-1-0/) — The earlier Seedance generation from ByteDance — how it differs from 2.0 and when the older version is still the sensible choice. - [Nano Banana Pro](https://higgsfield.wiki/models/nano-banana-pro/) — The higher tier of Google’s Nano Banana image model — what the Pro variant adds, and when the extra cost is justified. - [Veo 3.1](https://higgsfield.wiki/models/veo-3-1/) — Google’s incremental Veo release — what point updates typically change in a video model, and how to tell which version you are actually using. - [Grok Imagine](https://higgsfield.wiki/models/grok-imagine/) — xAI’s image generation model — what it is, how its content policy differs from the rest of the category, and what that means in practice. - [Higgsfield for DaVinci Resolve](https://higgsfield.wiki/plugins/davinci-resolve/) — Bringing AI generation into a DaVinci Resolve workflow — what an editor-side integration changes, and where it fits in a real timeline. - [Higgsfield for Photoshop](https://higgsfield.wiki/plugins/photoshop/) — Using AI generation inside a Photoshop workflow — what it adds beyond the built-in generative tools, and how to combine the two. - [Getting started with Higgsfield](https://higgsfield.wiki/guides/getting-started/) — A first-session orientation: what to try first, the two decisions that shape every generation, and the mistakes that waste the most credits early on. ## For agents - Markdown twin of any page: append `.md` to its path (e.g. https://higgsfield.wiki/face-swap.md) - [sitemap.xml](https://higgsfield.wiki/sitemap.xml) - Content usage policy: https://higgsfield.wiki/robots.txt ## Editorial policy - No invented prices, credit costs, or limits. Where a number changes often, this site says where to check rather than reproducing a figure that will go stale. - Model capabilities are described as of the verified date and flagged as version-dependent, because these ship every few months. - Structured data uses schema.org `about` to reference Higgsfield. This site does not publish an Organization node claiming to be Higgsfield.