Best AI Image Editing Models (2026)

The best AI image editing models for precise edits are GPT Image 2.5 Flare and FLUX.3 Image in Fuser, two of 128 image models on the canvas: ten models, one photo, one edit, plus a multi-reference test.

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Quick answer: the best AI image editing models for edits where everything you didn't mention must stay put are GPT Image 2.5 Flare and FLUX.3 Image in Fuser, two of 128 image models on the canvas. In our test they were the first two models to make all three requested changes without altering anything else, and when we added Krea 3 at High reasoning and FLUX.3 Klein on 23 October 2026, both did the same. To combine several pictures into one scene, use Krea 3: it takes up to eight references, tagged <image-1> to <image-8>. Grok Imagine 2.0 and Seedream 5.0 Lite were close behind. Nano Banana 2 and FLUX.2 Pro produced the boldest rain and lettering but rebuilt part of the room to do it. Qwen Image 2 and FLUX.1 Kontext Pro drifted furthest on this particular task.

The test: one photo, one instruction, ten models

Instruction-based editing means you give the model an image and a sentence, with no mask or selection, and it decides what to change. The hard part is the rest of the picture. So we picked an edit that mixes three kinds of change and one explicit constraint. The source is an AI-generated café photo of a woman in a yellow rain jacket with a teal bag strap across her chest, a bicycle in the window and a plain wall behind her. Every model got this instruction, verbatim:

"Change her yellow rain jacket to a charcoal-grey wool coat. Make it a rainy evening outside the window, with wet street reflections. Write the words OPEN LATE in white painted letters on the window glass. Keep her face, hair, pose, the coffee cup, the table and the bicycle exactly the same."

Each model ran once through its API with default settings, output size matched to the input where the model offers that option, and no retries or cherry-picking. The models were GPT Image 2.5 Flare, Nano Banana 2, FLUX.2 Pro, FLUX.1 Kontext Pro, Qwen Image 2, Seedream 5.0 Lite and Grok Imagine 2.0.

On 2 October 2026 we added FLUX.3 Image, Black Forest Labs' newest image model in Fuser, with the same source and the same instruction. Fuser's node scales a canvas image to fit 1,024 pixels before sending it, so we sent the source at that size, with the node's defaults: 1K, Aspect Ratio on Auto and Expand Prompt off. One run, no retries.

On 23 October 2026 we added Krea 3 and FLUX.3 Klein with the same source and instruction: Krea 3 in the Krea node with the Berry variant, Image Size on Auto and Medium reasoning (the default), then again at High; Klein in the FLUX.3 Image node at 1K, Aspect Ratio on Auto and Expand Prompt on, its defaults. One run each, no retries.

Same source image and the same instruction for every model, one run each, no retries. Run on 28 September 2026.

What each model did

GPT Image 2.5 Flare made the coat swap, the rainy evening and legible hand-painted "OPEN LATE" lettering on the left window. The back wall, the empty tables, the bag strap, the bicycle and her face are unchanged. It is the result you could drop into a layout without a second pass. In Fuser the GPT Image node also accepts a mask, so you can restrict an edit to one region when a sentence alone isn't precise enough.

FLUX.3 Image made the coat swap, a rainy evening with wet reflections and rain on the glass, and "OPEN LATE" in clean white capitals on the left window, closer to sign lettering than the hand-painted look GPT Image drew. Her face, hair and pose, the bag strap, the cup, the table, the bicycle and the back wall are unchanged, and it returned the source size, 1392 × 752. Measured pixel by pixel, a third of the frame changed by more than 3.2%, almost all of it the coat and the windows; the right third of the frame, with the back wall and tables, came back 99.8% within that tolerance. Black Forest Labs says "there is no edit mode, mask, or strength setting: the prompt says what to do with the images" (BFL editing guide), so for a fixed region you add bounding boxes to the prompt instead. Our FLUX.3 Image editing guide covers both.

Same source and instruction. GPT Image 2.5 Flare from the original test (28 September 2026); FLUX.3 Image at 1K, one run, 2 October 2026. Bottom right: red marks pixels FLUX.3 Image changed by more than 3.2%.
Same source and instruction. Krea 3 (Berry, Image Size Auto) at Medium and High reasoning, and FLUX.3 Klein at 1K; one run each, 23 October 2026. At Medium, Krea 3 dropped the bag strap.

Krea 3 at its default Medium reasoning made the coat swap, the rain and large white "OPEN LATE" capitals on the right-hand pane, but removed the teal bag strap, the same slip Seedream 5.0 Lite and FLUX.2 [pro] made. At High reasoning it kept the strap, put the lettering on the left pane and, by eye, left her face, the cup, the table, the bicycle and the back wall as they were. Both runs came back at twice the source's width and height (2784 × 1504). High took about three times as long (170 seconds against 54) and costs more per edit, so save it for edits where the rest of the photo has to hold.

FLUX.3 Klein also made all three changes and kept her face, the strap, the cup, the table, the bicycle and the back wall, at the source size of 1392 × 752. Its "OPEN LATE" is lighter and partly transparent, closer to frosted lettering than paint. It returned the edit in under 7 seconds.

Grok Imagine 2.0 kept the room, the strap and the bike, and set clean white lettering on the window. Two costs: it returned 1280 × 720 rather than the source's 1392 × 752, and the framing shifted slightly, so it won't line up pixel for pixel with the original.

Seedream 5.0 Lite kept the room and wrote the crispest lettering of the set, but removed the bag strap even though it wasn't part of the change. It returned the edit at twice the input's width and height (2784 × 1504), because we left the output size at its 2K default. That is useful if you need a large file.

Nano Banana 2 (Gemini 3.1 Flash Image) produced the most convincing rain: wet street, reflections, bold lettering and the strap intact. It also turned the plain back wall into a second window to fit the street scene. Google's editing guidance recommends stating what must not change, and multi-turn editing to refine a result, so a follow-up "keep the back wall as it was" is the natural next step.

FLUX.2 [pro] got the coat and a dramatic painted sign, but dropped the strap and also replaced the back wall with a window. The sign came with stray brush-stroke framing lines.

FLUX.1 Kontext [pro] kept her pose and the strap, but read "wool coat" as a dark hooded jacket, darkened the whole frame, and rendered faint, ghosted lettering. Black Forest Labs' own docs now recommend FLUX.2 for new projects, and list iterative editing, a series of single edits from one reference, among Kontext's core uses.

Qwen Image 2 kept her face, the cup and the coat change, but replaced the café interior with a street-side view and dropped the strap. It snapped the output to 1408 × 768.

Treat this as one task, not a benchmark. It rewards restraint on a multi-part edit; a single-change edit or a text-replacement edit could rank the models differently.

Multi-reference image editing: three images into one scene

An instruction edit changes one picture. Multi-reference editing builds a new one from several: a person from one image, a product from another, a location from a third. Krea 3 takes up to eight references, and you name them in the prompt by position, <image-1> to <image-8>, in the order they are connected to the node. On 23 October 2026 we gave it the reference portrait from our image model test, the LUMA 02 serum bottle and the café photo above, with this prompt:

"The woman from <image-1>, in her mustard knit sweater, sits at the round wooden window table of the café in <image-3>, holding the amber serum bottle from <image-2> up to the window light and reading its label. Keep her face, copper curls, freckles and round tortoiseshell glasses; keep the bottle's amber glass, black dropper cap and the label text "LUMA 02"; keep the café's brick wall, bicycle and window. Soft daylight, 35mm documentary photograph."

Three references, one prompt: Krea 3 (Berry, Medium reasoning, Image Size Auto), one run, 23 October 2026. All three input images are AI-generated.

Krea 3 seated the woman from the portrait at the café's window table in her mustard sweater, with her curls, freckles and tortoiseshell glasses, holding the bottle up with a clean, readable "LUMA 02" label. The window, brick pier, bicycle and tables come from the café photo. FLUX.3 Klein, given the same three images (named "image 1" to "image 3", since it has no tags), kept her likeness and the sweater but hand-lettered a wobbly "LUMA 02" and moved the bicycle outside the window. The Krea 3 prompt guide covers multi-reference prompts in more depth.

How to get cleaner edits from any of them

These come from the vendors' own documentation and from what we saw in this run:

  • Name what stays. Google's guidance gives the pattern: describe the change, then add "Do not change any other elements of the image." Even with that line, seven of ten models (counting Krea 3 at its default reasoning) changed something beyond the three requested edits, so check every region, not just the one you asked about.

  • Split big edits into steps. Google calls multi-turn conversation the recommended way to iterate on images, and Black Forest Labs lists iterative editing as a core Kontext use. Three changes in one sentence is where drift showed up in our test.

  • Quote the text you want. Kontext's docs say the most effective way to edit text is to put it in quotation marks, in the form Replace 'OPEN' with 'CLOSED'.

  • Refer to reference images by number. When you feed several images, FLUX.2's editing docs use "image 1", "image 2" in the prompt to say which picture supplies which element. Krea 3 uses tags instead: <image-1>, <image-2> and so on, in the order the images are connected.

  • Check the output size. Four of ten models returned a different size from the input. If the edit has to replace the original in a layout, resize or crop it before it goes further.

Capacity and settings in Fuser

The models differ in how many images they accept and which settings Fuser exposes:

  • Nano Banana 2 accepts up to 10 reference images and outputs at 1K, 2K or 4K. The same node also offers Gemini 3 Pro Image.

  • GPT Image 2.5 Flare is the default in the GPT Image node, with a mask input and a quality setting.

  • FLUX.3 Image edits when you connect up to 10 images and generates from text when none are connected. It offers 512px to 4K resolution tiers, and an Auto aspect ratio that follows the first image. It has no mask input and no seed, and its Expand Prompt switch is off by default.

  • FLUX.3 Klein is the Klein option in the FLUX.3 Image node: up to 10 images, 512px to 4K, a seed, and Expand Prompt on by default. Black Forest Labs says not to use Klein without that prompt upsampler (BFL).

  • Krea 3 is the default in the Krea node. It edits or combines up to 8 reference images, tagged <image-1> to <image-8> in connection order, with Berry (quality) and Jam (speed) variants, a reasoning level from Low to Ultra (High and Ultra apply when references are connected), a negative prompt for Berry, a seed and an Auto image size.

  • FLUX.2 has a Model Type setting: Turbo is the default, and we set it to Pro for this test. Dev, Max, Flex and the Klein variants are also available. BFL documents up to 8 reference images through the API.

  • FLUX.1 Kontext takes up to 4 images and offers Pro or Max. Max has better prompt adherence and typography, at double the cost of Pro.

  • Qwen Image 2 switches to edit mode when you connect one to three images, with Standard and Pro tiers.

  • Seedream 5.0 Lite accepts up to 10 reference images, with auto output sizes of 2K, 3K or 4K.

  • Grok Imagine 2.0 edits one or more images at 1K or 2K.

Run your own comparison

On a Fuser canvas, connect one image and one text node to several editing nodes and run them together, as in the canvas above. You compare results side by side instead of across browser tabs, then send the winner to the next step: an upscaler, an image-to-video model or another edit. For single-model detail, see the FLUX.3 Image editing guide, the FLUX Kontext editing guide and the Qwen Image Edit guide; for a single-object swap measured pixel by pixel, see FLUX.3 Image vs GPT Image. For lettering-heavy work, see the best models for text in images, and for keeping a person the same across many edits, consistent characters. Save the graph as a Recipe to run the same comparison on your next photo. For Krea 3's reference tags and reasoning levels, see the Krea 3 prompt guide.

Last verified October 23, 2026.

Pick the editing model for the job.

Based on one shared edit test plus each vendor’s documentation. FLUX.3 Image was added on 2 October 2026, Krea 3 and FLUX.3 Klein on 23 October 2026.

ModelReach for it whenWatch out for
Closest to the original
GPT Image 2.5 Flare

Edits where everything you didn't mention must stay; masked edits.

Higher quality settings add latency and cost.

FLUX.3 Image

Edits where the rest of the photo must stay put; up to 10 references; bounding boxes for exact regions.

No mask or seed; BFL notes shadows, reflections or nearby lighting may still change.

Krea 3

Combining up to eight tagged references into one scene; clean edits at High reasoning.

At Medium it dropped a detail; High is slower and costs more.

FLUX.3 Klein

Fast edits that keep the scene and the source size; up to 10 references; a seed.

Lettering came out light and partly transparent.

Grok Imagine 2.0

Clean edits that keep the scene and small details.

Returned 1280 × 720 and reframed slightly.

Seedream 5.0 Lite

Crisp lettering, large output, up to 10 references.

Dropped a detail we didn't ask to change.

Strongest transformations
Nano Banana 2

Big scene and lighting changes, multi-turn refinement, up to 10 references.

Rebuilt part of the room to fit the edit.

FLUX.2 [pro]

Bold restyles and multi-reference composites.

Dropped the strap; stray marks around the sign.

Better on narrower edits
FLUX.1 Kontext [pro]

Single targeted changes and quoted text replacement.

Misread the garment; faint lettering on a multi-part edit.

Qwen Image 2

Chinese and English typography; one to three input images.

Replaced the café interior on this task.

Questions, answered.

It depends on the edit. In our shared test, GPT Image 2.5 Flare and FLUX.3 Image changed only what was asked, and so did Krea 3 at High reasoning and FLUX.3 Klein when we added them; all run in Fuser, among 128 image models on one canvas. Grok Imagine 2.0 and Seedream 5.0 Lite were close. Nano Banana 2 and FLUX.2 [pro] produced the strongest scene changes but also altered parts of the room. For combining several images into one scene, use Krea 3.

You give a model an image and a plain-language instruction, such as "change the jacket to a grey wool coat", with no mask or selection. The model decides which pixels to change and which to keep.

Say what must stay the same, make one change per pass, and use a mask when the model supports one. In Fuser the GPT Image node takes a mask input. Then check the whole image, not just the area you edited.

You give a model several images and one prompt, and it combines them: a person from one, a product from another, a location from a third. Krea 3 in Fuser takes up to eight references, named in the prompt as <image-1> to <image-8>; in our test it seated a woman from a portrait in a café from another photo, holding a serum bottle from a third with its label intact. FLUX.3 Image and FLUX.3 Klein take up to ten.

Yes. All ten models in our test wrote the requested words on the window, though legibility varied. For replacing existing text, Black Forest Labs recommends quoting it: Replace 'OLD' with 'NEW'.

Not always. In our test FLUX.3 Image, FLUX.3 Klein, FLUX.2 [pro], FLUX.1 Kontext, Nano Banana 2 and GPT Image 2.5 kept 1392 × 752, Qwen Image 2 returned 1408 × 768, Grok Imagine 2.0 returned 1280 × 720, and Seedream 5.0 Lite and Krea 3 returned 2784 × 1504.

Yes. In Fuser, connect one image and one instruction to several editing nodes on the same canvas, run them, and send the best result to the next step.

Compare edits on one canvas.

Send one photo to several editing models, keep the best result and carry it into the next step.

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