0 / 20000
AI Image Generator — Pick the Right Model for Every Image
This AI image generator runs Google's Nano Banana, OpenAI's GPT Image, ByteDance's Seedream, and Black Forest Labs' Flux from a single workspace. Write a text prompt or upload up to 16 reference photos, generate in resolutions up to 4K, and download every image watermark-free with commercial rights included. And because no single model wins at everything, the guide below breaks down what each one actually does best — based on official documentation, blind-test rankings, and community feedback.
The State of AI Image Generation in 2026
Image models now ship in months, not years. Here is what actually changed recently — and which older claims you can safely ignore.
Google ships Nano Banana 2
Built on Gemini 3.1 Flash Image, Google describes it as combining Nano Banana Pro’s advanced features with Gemini Flash speed. It has been rolling out across the Gemini app, Search, and Google’s creative tools — replacing Nano Banana Pro as the default in several of them.
GPT Image 2 lands in the API
OpenAI positions it for production work where images must stay accurate, readable, and on-brand. It currently holds the top Elo score in Artificial Analysis’ blind-vote image arena, ahead of both of Google’s flagships.
Flux 2 rethinks prompting
Black Forest Labs launched Flux 2 — a 32-billion-parameter rectified flow model with multi-reference support and an official prompting guide that drops negative prompts entirely: you describe what you want, never what you don’t.
Seedream learns to reason
ByteDance’s Seedream line added chain-of-thought reasoning and live web search during generation. Seedream 5 Lite thinks through complex prompts before rendering, while Seedream 4.5 remains the family’s pick for photoreal detail.
Three claims about AI images that are now outdated
The claim
AI can't draw hands.
The reality
Largely fixed in current flagship models. Community testing still catches occasional anatomy slips in crowded scenes, but hands alone are no longer a reason to avoid AI images.
The claim
AI text always comes out garbled.
The reality
Short labels and headlines now render reliably — GPT Image 2 in particular was built around readable typography. Small print and long paragraphs remain the real limit.
The claim
You need to find the one 'best' model.
The reality
Blind-vote rankings and community tests agree: the leader changes by task. Text-heavy layouts, photoreal portraits, and fast drafts each favor a different model — which is exactly why this generator carries several.
Which AI Image Model Should You Use?
There is no single best AI image generator — the right model changes with the task. Specs below come from official documentation; rankings reference Artificial Analysis blind-vote Elo.
| Model | Best for | Text rendering | References | Max output | Speed |
|---|---|---|---|---|---|
| Nano Banana 2 | Photoreal scenes, fast iteration | Good — short labels reliable | Up to 14 | 4K | Fastest flagship |
| Nano Banana Pro | Maximum detail at 4K | Good | Up to 8 | 4K | Slower, quality-first |
| Nano Banana | Quick drafts, recurring characters | Basic | Up to 10 | Standard | Very fast |
| GPT Image 2 | Text, layouts, diagrams | Best in class | Up to 16 | 4K | Slowest — precision-first |
| Seedream 5 Lite | Complex prompts, stylized art | Fair — avoid small print | Up to 14 | 3K | Fast |
| Flux 2 Pro & Flex | Color-accurate product shots | Clean short text | Up to 8 | 2K | Fast (Pro) / tunable (Flex) |
Quick picks
Readable text, posters, UI mockups
GPT Image 2 — community consensus is that it finally renders typography correctly.
Photoreal people and products
Nano Banana 2 — testers consistently describe its skin and lighting as the most camera-like.
Final delivery at maximum 4K detail
Nano Banana Pro — slower, but built quality-first.
Fast, low-stakes drafts
Nano Banana — iterate on composition quickly, then re-run the winner on a flagship.
Many references, consistent style
Seedream 5 Lite — it accepts up to 14 reference images.
Precise parameter control
Flux 2 Flex — adjustable steps and guidance for repeatable results.
The Model Lineup: Strengths, Trade-offs, Verdicts
Official positioning, community verdicts, and the jobs each model should — and should not — take.
Nano Banana 2
Google · The fast flagship
Google’s newest image model, built on Gemini 3.1 Flash Image. Officially it merges Nano Banana Pro’s capabilities with Flash-level speed, and it taps live web knowledge while generating — so real subjects, places, and infographics come out accurate. It can even translate and localize text inside an image. Community testing keeps reaching one verdict: its portraits and lighting look the most like an actual photograph.
Best for: Photoreal images, quick variant runs, grounded real-world subjects
Not for: Dense small print — switch to GPT Image 2 for that
Nano Banana Pro
Google · Quality-first 4K
The detail-oriented sibling. Nano Banana Pro renders at up to 4K with up to 8 reference images and holds up under demanding briefs — product close-ups, textured materials, architectural detail. Google has begun replacing it with Nano Banana 2 as the consumer default, but in API workflows it remains the choice when render quality outranks turnaround time.
Best for: Final 4K assets, detail-heavy renders
Not for: Rapid iteration — generation takes noticeably longer
Nano Banana
Google · The drafting layer
The original Nano Banana stays in the lineup for a reason: it generates in seconds and keeps a subject recognizable across runs, which makes it the natural drafting layer. Block out compositions, explore prompt ideas quickly, and only send the winning direction to a flagship model for the final pass.
Best for: Drafts, prompt exploration, recurring characters
Not for: Print-resolution output or accurate typography
GPT Image 2
OpenAI · Typography and layout leader
OpenAI built GPT Image 2 for production work — its words — targeting images that must stay accurate, readable, and on-brand. Analysts widely credit its autoregressive approach — building images the way language models build sentences — for why posters, menus, diagrams, and UI mockups hold together. It leads Artificial Analysis’ blind-vote Elo ranking, and users repeatedly report it as the first model where English text just works. Accepts up to 16 reference images.
Best for: Posters, packaging, diagrams, multi-element layouts
Not for: Speed-sensitive workflows — it is the slowest model here
Seedream 5 Lite
ByteDance · Reasoning before rendering
Seedream 5 Lite runs chain-of-thought reasoning over your prompt and can search the web mid-generation, so layered instructions and niche subjects land more often. It accepts up to 14 references and outputs at up to 3K. Community reviews praise its handling of complex scenes while noting the finish can read slightly stylized — Seedream 4.5, its photoreal-leaning predecessor, is also available here.
Best for: Complex multi-part prompts, illustration, stylized art
Not for: Small text and strict photorealism
Flux 2
Black Forest Labs · Controlled and color-accurate
Flux 2 comes in two builds: Pro for speed, Flex for adjustable steps and guidance. It is a 32-billion-parameter model with reliable color fidelity and clean short text, and BFL publishes the most explicit official prompting guide of any vendor — structure prompts as subject, action, style, context, and skip negative prompts entirely. Up to 8 reference images, output to 2K.
Best for: Brand-color accuracy, controlled product shots
Not for: 4K delivery or long in-image text
Real-World Performance, Dimension by Dimension
What official docs claim, what blind tests show, and what users actually report.
Text rendering
GPT Image 2 is the clear leader — users widely report near-perfect English headlines and short labels. Nano Banana 2 handles short text well and can even translate text inside an image, but every model still degrades on small print.
Photorealism
Community comparisons consistently favor Nano Banana 2 for skin, materials, and cinematic lighting; Nano Banana Pro matches it at 4K given more patience. Seedream 5 Lite leans stylized — treat that as a feature for illustration work.
Character and style consistency
Reference images are the reliable path: GPT Image 2 takes up to 16, Seedream 5 Lite and Nano Banana 2 up to 14. No model here offers a true style lock yet, so expect drift between runs and save the exact wording that works.
Speed
Nano Banana and Flux 2 Pro return drafts fastest; Nano Banana 2 is the fastest flagship. GPT Image 2 trades speed for layout precision — community timing puts it several times slower than Nano Banana 2.
Spatial instructions
The shared weak spot. Across community tests, no current model reliably follows precise layout commands like 'logo exactly in the top-left corner.' GPT Image 2 comes closest but is not deterministic — write flexible prompts instead of pixel specs.
Rankings referenced on this page come from Artificial Analysis' blind-vote image arena (Elo methodology). Speed and reliability notes summarize recurring community findings, not lab benchmarks.
Real AI Image Use Cases, Matched to the Right Model
Each card pairs the deliverable with the right model, the settings that work, and the trap to avoid.
Posters, Menus & Social Graphics
Fits: Layouts where words must be readable: event posters, price lists, quote cards, simple infographics.
Why it works: GPT Image 2's text-first architecture keeps lettering coherent where diffusion models tend to smear it.
Setup: GPT Image 2 at 2K; keep critical text under roughly eight words per element and quote it exactly in the prompt.
Skip it for: Dense paragraphs or legal fine print — render those in a design tool on top of an AI background instead.
Product & Brand Visuals
Fits: Hero shots, colorway variants, lifestyle scenes built from existing product photos.
Why it works: Image-to-image mode anchors the AI to your actual product, and Flux 2 holds brand colors steady across a series.
Setup: Upload two to four clean reference photos; Flux 2 Pro for color fidelity, or Nano Banana 2 for camera-real lighting.
Skip it for: Pixel-exact packaging mockups with regulatory text — spatial control isn't deterministic yet.
Character Sets & Story Art
Fits: A recurring character across covers, panels, and marketing art.
Why it works: Multi-reference input is what keeps a face recognizable between scenes.
Setup: Generate the master design first, then feed it back as reference — Seedream 5 Lite or Nano Banana 2 with three to six references.
Skip it for: Crowd scenes with several distinct recurring characters — consistency drops fast beyond a few subjects. Generate each character separately and assemble the group in an editor instead.
Photoreal Scenes & Editorial Images
Fits: Article headers, mood imagery, and the classic AI photo generator job — realistic scenes you can't go out and shoot.
Why it works: Current flagships finally pass the glance test — community reviewers describe Nano Banana 2’s lighting as camera-like.
Setup: Nano Banana 2 for speed, Nano Banana Pro at 4K for print; name a camera style in the prompt for extra realism.
Skip it for: Recognizable real people and news-event imagery — both accuracy and policy will fight you. For real events, license actual photography instead.
Known Limitations — and How to Work Around Them
Every model on this page fails somewhere. Knowing where saves you re-runs and review time.
Small print, QR codes, charts, and exact data labels come out wrong or invented.
Workaround: Treat in-image data as decorative. Generate the visual, then overlay real text, codes, and figures in an editor before publishing.
No style lock exists — identical prompts drift between runs.
Workaround: Save the full prompt of any image you like and reuse it verbatim, then steer with reference images; in image-to-image mode the reference anchors most of the look.
Flux 2 ignores negative prompts ('no people', 'no text') by design.
Workaround: Describe the scene you want instead: 'an empty street at dawn' beats 'a street, no people' — BFL's own guide says to state the positive.
Safety filters occasionally flag harmless prompts — medical topics, brand names, certain skin descriptions.
Workaround: Rephrase around the trigger word, drop brand names, or switch models; filters differ by vendor, and a prompt blocked on one often passes on another.
Precise spatial layout ('text top-left, logo bottom-right') is unreliable everywhere.
Workaround: Ask for 'clear space at the top' style guidance instead of coordinates, generate a few variants, and do final placement in a design tool.
Prompt Playbook: From First Draft to Final 4K
The rules below merge BFL's and OpenAI's official prompting guides with what holds up in daily use.
The order-of-importance formula
Front-load what matters. BFL's official guide is explicit that models weigh early words more heavily, and that 30–80 words is the sweet spot: Subject → Action → Style → Context → secondary details.
"A ceramic espresso cup on a walnut café table, steam rising, shot like a 50mm food editorial, warm morning window light, shallow depth of field"
A weak prompt, rewritten
Weak
"beautiful coffee photo, high quality, 4k, trending, no clutter"
Strong
"Overhead shot of a flat white in a gray stone cup, centered on a white marble counter, soft diffused daylight, minimalist negative space around the cup"
Quality words ('beautiful', '4k', 'trending') tell the model nothing, and 'no clutter' is a negative prompt Flux 2 will skip by design. The rewrite states subject, framing, surface, light, and the empty space the first prompt only hinted at.
The draft-to-final workflow
- 1Draft on Nano Banana: run four to eight fast variants to settle composition and wording.
- 2Pressure-check the winner: zoom in on hands, edges, text, and reflections before committing.
- 3Re-run on the right flagship: GPT Image 2 if text leads, Nano Banana 2 or Pro for photoreal — then export at 2K or 4K.
Per-model prompting notes
- GPT Image 2: put exact wording in quotes for any text you want rendered — it follows quoted strings closely.
- Nano Banana 2: name real places, products, or facts freely; its web-grounded knowledge keeps them accurate.
- Seedream 5 Lite: long, layered prompts are fine — it reasons through them before rendering.
- Flux 2: name a camera, lens, or film stock for photorealism, and never write what you don’t want.
How to Generate AI Images Here
Use it as a quick picture generator or a full production tool — either way it sits at the top of this page. Here's the fastest path through it.
Pick a mode and a model
Text-to-image builds from words alone; image-to-image starts from photos you upload. Open the model menu and match it to the job — the comparison table above is the cheat sheet.
Write the prompt, front-loaded
Lead with subject and action, then style and light, in 30–80 words. Add reference images whenever a product, face, or style must carry over.
Generate, compare, upscale
Run a couple of variants, zoom in on text and hands, then re-generate the best one at 2K or 4K and download — watermark-free and ready for commercial use.
AI Image Generator: Honest FAQ
Direct answers on model choice, limits, and settings — sourced from official docs, blind-vote rankings, and real testing.
Pair It With the Rest of the Toolkit
Images are step one — animate them, voice them, or hand them to a talking avatar.
Stop Guessing Which Model Is Right
One AI image generator, every leading model in one place — Nano Banana 2 for photoreal speed, GPT Image 2 for typography, Seedream and Flux for everything in between. Pick by task, generate in up to 4K, and keep full commercial rights.