
Reve 2.1 Edit API by REVE AI
Reve 2.1 Edit applies precise, instruction-driven, element-level edits to a single input image at native 4K, changing targeted regions while preserving the rest of the scene.
Reve 2.1 — Edit
Developer: Reve AI
Model ID: reve-ai/reve-2.1/edit
Release Date: July 9, 2026
Overview
Reve 2.1 Edit takes a single input image plus a natural-language instruction and returns an edited image at native 4K. Rather than repainting the whole frame, Reve treats an image as a structured set of regions — an "image as code" approach in which every element is addressable and editable. That means the model can apply precise, localized changes while leaving the rest of the picture intact, and it can iterate on an image repeatedly without quality drifting.
This edit variant is the image-conditioned entry point to Reve 2.1: you provide one image and describe how it should change. Use it whenever you already have a picture and want to modify it — as opposed to generating from scratch (reve-ai/reve-2.1/text-to-image) or combining several references (reve-ai/reve-2.1/remix).
The Reve 2.1 Model
Reve 2.1 is an update to Reve's flagship image model that sharpens the model's visual intelligence — how well it reasons about structure, hierarchy, and spatial relationships before rendering. On public leaderboards it ranks second overall while using less than a tenth of the compute of the models ranked around it, and it remains the top-rated 4K image generator.
Its foundation is a "large layout model." Images are represented as structured regions that can be reasoned about much like code, which means controllability is built into the model's visual intelligence rather than bolted on afterward. Practical consequences of this design include:
- Higher visual intelligence — the model plans in finer detail and reasons more accurately about how elements relate to one another.
- Native 4K output — full 16-megapixel images (4096 × 4096 class) with sharp edges and preserved texture, generated directly rather than through an upscaling step.
- Stronger text rendering — improved legibility and extended multilingual support, including foreign scripts.
- Precision editing — because every region is independently addressable, edits target individual elements without disturbing the rest of the scene, and repeated edits keep their quality.
Key Capabilities
- Instruction-driven editing — Describe the change in plain language and Reve applies it to the supplied image, from small local tweaks to substantial reworks.
- Element-level precision — Addressable regions let the model change one element while preserving surrounding content, composition, and style.
- Best-in-class typography — Add, remove, or replace in-image text — signs, labels, packaging copy, logos — with legible, correctly spelled results across multiple languages and scripts.
- High instruction adherence — Faithfully interprets long, detailed edit instructions (up to 2,560 characters). Instructions are automatically enhanced by the model.
- Native 4K, no upscaling — Renders true 16-megapixel results directly, holding fine detail at full size.
- Built-in post-processing — Apply background removal and a large library of stylistic effects (textures, light, and color) directly in the same request.
Input
This model takes two creative inputs:
- Image — a single input image to edit, provided as a URL or a base64-encoded string. This is the picture the model modifies.
- Text prompt — a natural-language instruction describing how to edit the image (up to 2,560 characters, automatically enhanced by the model).
Exactly one image is used. To generate an image without a reference, use reve-ai/reve-2.1/text-to-image; to combine multiple reference images, use reve-ai/reve-2.1/remix. The remaining fields below control aspect ratio, output format, and optional post-processing.
Input Parameters
| Parameter | Type | Default | Range / Options | Description |
|---|---|---|---|---|
prompt | string | — | ≤ 2560 characters | Required. Instruction describing how to edit the image. Automatically enhanced by the model. |
image | string | — | URL or base64 | Required. The input image to edit. |
aspect_ratio | string | auto | auto, 4:1, 3:1, 21:9, 2:1, 17:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16, 1:2, 1:3, 1:4 | Desired aspect ratio. auto keeps the aspect ratio of the input image. |
resolution | string | 4k | 4k | Output resolution. Reve 2.1 renders natively at 4K (~16 megapixels). |
remove_background | boolean | false | — | Keeps only the central subject and makes the background transparent (post-processing). |
effects | array | [] | 0–51 items | Optional list of post-processing effects (categories: textures, light, color), applied in order. Each item selects an effect and may override its parameters. |
output_format | string | png | png, jpeg, webp | Format of the output image. |
enable_base64_output | boolean | false | — | Return the image as a Base64 string instead of a URL (API only). |
enable_sync_mode | boolean | false | — | Wait for the result before returning, so the image is delivered directly in the response (API only). |
Output
Returns the edited image, either as a URL or — when enable_base64_output is enabled — as a Base64-encoded string. By default the request is asynchronous: the response provides a request ID that can be polled until the image is ready. Enabling sync mode returns the finished image directly.
Output formats: PNG, JPEG, WebP. Resolution: native 4K (~16 megapixels).
Use Cases
- Product & e-commerce retouching — Swap backgrounds, change colorways, or clean up product shots while keeping the subject faithful.
- Localized text edits — Update signage, packaging copy, or on-image labels — including translating text into other scripts.
- Creative iteration — Refine an existing image step by step, adding, removing, or restyling individual elements without regenerating the whole frame.
- Marketing variations — Produce edited variants of a hero image for different placements and formats.
- Agentic pipelines — Programmatic, element-level editing where an agent reads an image's structure and issues precise edits without a human in the loop.
Pricing
Pricing for this model is driven by what each request actually uses. Every request produces one native-4K edited image at a fixed base price; optional post-processing (background removal and stylistic effects) adds to the total. There is no separate resolution or upscaling charge, because 4K is generated natively.
SKUs
| SKU | Description | Unit Price |
|---|---|---|
sku_image | Base price per generated image (Edit, native 4K, no post-processing) | $0.24 |
sku_remove_background_mp | Per megapixel for background removal | $0.0036 |
sku_effect | Per applied post-processing effect | $0.0048 |
Formula
cost = sku_image + sku_remove_background_mp × 16 × (remove_background ? 1 : 0) + sku_effect × number_of_effects
- Base image — every request includes one
sku_imagecharge of $0.24. - Background removal — when
remove_backgroundis enabled, it is billed across the full 16 megapixels of the 4K image:0.0036 × 16 = $0.0576. When disabled, this term is $0. - Effects — each effect in the
effectslist adds onesku_effectcharge of $0.0048; an empty list adds nothing.
Examples
| Scenario | Calculation | Cost |
|---|---|---|
| Base edit (no post-processing) | 0.24 | $0.2400 |
| Background removal | 0.24 + 0.0036 × 16 | $0.2976 |
| 1 effect | 0.24 + 0.0048 × 1 | $0.2448 |
| 3 effects | 0.24 + 0.0048 × 3 | $0.2544 |
| Background removal + 2 effects | 0.24 + 0.0036 × 16 + 0.0048 × 2 | $0.3072 |
A plain edit with no post-processing costs the base $0.24. Background removal and each stylistic effect are the only add-ons, so leaving both untouched yields the base price.



















