ChatGPT Images 2.0 Tutorial: From Beginner to Pro

If you’re looking for the GPT Image 2 official site or just don’t know how to use GPT Image 2, this tutorial is for you.

In the early hours of April 22, 2026 (Beijing Time), OpenAI officially released GPT-image-2. This is OpenAI’s latest image generation model for 2026, with significant improvements over the previous generation in four key areas: Chinese text rendering, real-world understanding, editing precision, and overall aesthetics. The generated images have evolved from “obviously fake” to “hard to tell if it’s AI or real.”

Let’s start from scratch and walk through it step by step.

What Is ChatGPT Images 2.0?

ChatGPT Images 2.0 (also known as GPT-image-2) is OpenAI’s latest image generation model. Instead of simply “assembling” an image from keywords, it now has a deeper understanding of real-world logic—how lighting should fall, where text should be placed, how much whitespace a poster needs—and can produce results at a near-professional level.

For Chinese users, the biggest change is text rendering. In the past, AI generating Chinese text was almost always a disaster. This time, it finally produces usable results.

Quick Start: Generate Your First Image in 4 Steps

Step 1: Find the Image Generation Entry

There are many ways to access GPT-image-2. The official route is through OpenAI’s platform. But if you’re accessing from China or want a more user-friendly, Chinese-compatible tool, you can use the image generation tool provided on our site:

Step 2: Enter Your Prompt

Once inside the tool, type your image description directly into the input box. For example:

Vertical poster design, China tourism theme, featuring classic attractions from at least 6 cities including Beijing, Shanghai, and Hong Kong. Each module contains refined illustrations with text information (name, description, history, recommended activities). Layout like high-end magazine editorial, infographic style, fusion of Chinese aesthetics and modern design, reasonable whitespace, visually unified, premium feel.

After writing it, click send and wait a moment for the image to generate.

Step 3: Adjust the Aspect Ratio

After the image is generated, click on it to enter the editing panel. You can adjust the aspect ratio (16:9, 4:3, 1:1, etc.), make local optimizations, or regenerate.

Step 4: Iterate

Don’t expect a perfect result on the first try. Use phrasing like “on this image, change XX to YY” to trigger its local editing capability. GPT-image-2 supports targeted adjustments on existing images, which is much more efficient than rewriting the entire prompt from scratch.

10 Real Test Cases (With Prompts)

These cases are all actually generated. You can copy the prompts directly.

Case 1: Chinese Poster Design

Prompt:

Vertical poster design, China tourism theme, featuring classic attractions from at least 6 cities including Beijing, Shanghai, and Hong Kong. Each module contains refined illustrations (with aesthetic appeal and wild cursive style famous poems) with text information (name, description, history and culture, recommended activities). Layout like high-end magazine editorial, infographic style, fusion of Chinese aesthetics and modern design, reasonable whitespace, visually unified, premium feel.

Text rendering has always been AI’s weak spot—English is barely acceptable, but Chinese text would completely break. Make a recruitment poster, menu, product packaging, or social media cover, and text is always the first thing to fail. GPT-image-2 has finally crossed that threshold, and the output is good enough to publish with minimal editing.

Case 2: Interior Design Rendering

Prompt:

High-end interior design, modern minimalist residential, floor plan combined with 3D rendering, open space, floor-to-ceiling windows, large areas of whitespace, warm lighting atmosphere, extremely clean and premium feel, as refined as a showroom.

GPT-image-2’s understanding of the real world has clearly leveled up. It starts to understand “what things in a real space should actually look like”—this isn’t just stacking elements, it’s about grasping spatial relationships.

Case 3: Live Stream Screenshot

Prompt:

Generate a Douyin (TikTok) live stream screenshot, a beautiful woman selling stockings on live stream, online viewers count is 66666, heat level is 34+, a viewer named Lin Xiaohao sends her a Carnival gift.

This kind of real-life scenario simulation was nearly impossible for previous generation models.

Case 4: Exam Paper Layout

Prompt:

High school first-year math midterm exam, A3 layout, with precisely annotated geometry diagrams, mixed typography with Songti body text and Kaiti title, sealed line section for school, class, name, and exam number, clear question numbers, page footer with page number and score column.

Complex layout with mixed Chinese text—GPT-image-2 handles it cleanly.

Case 5: Character Relationship Chart

Prompt:

Map out the character relationships from Dream of the Red Chamber and display them clearly in an image.

AI can now handle information architecture diagrams too.

Case 6: AI Agent Workflow Diagram

Prompt:

AI agent workflow diagram, task breakdown process, multi-step execution paths, clear logical arrows, professional flowchart style.

Previous models could do this too, but the results were usually obviously fake—positions looked wrong, text seemed randomly generated, structure was messy. This time, the output shows a remarkably accurate understanding of “what a real flowchart should look like.”

Case 7: E-commerce White Background Image + Detail Page

First, ask the model to turn a casual desktop photo into a white background e-commerce main image:

Prompt:

Take a casual photo of a desktop ornament and turn it into a white background e-commerce product image, re-light it, make the product look more refined.

After the image comes out, add another line:

Now create a detail page poster for me.

White background, soft lighting, shadows, cleaner product subject—the result looks like the work of a reliable retoucher. Previously, creating a set like this (photography, retouching, layout, copywriting, detail page logic) would take designers and operators at least a day or two of back-and-forth. Now it’s just one photo plus two sentences to generate a draft.

Case 8: Dark Tech-Style Cover Poster

Prompt:

Cover poster, dark tone, information-rich, tech feel, but don't make it tacky, don't make it look like a cyberpunk template from ten years ago.

Composition rhythm, color restraint, information hierarchy, atmosphere—GPT-image-2 handles all of these well.

Case 9: Celebrity Resume Cover Poster

Prompt:

Celebrity resume cover poster, dark tone, information-rich, tech feel, but don't make it tacky, don't make it look like a cyberpunk template from ten years ago.

Case 10: Palace Cheongsam Film Photography

Prompt:

Snowy Beijing Forbidden City, a woman in a qipao holding an umbrella standing in front of the red wall of Kunning Palace, with red plum blossoms nearby, snow covering the ground, film grain texture, Kodak Portra 400 color tone.

The one thing that used to reassure professional designers about AI image generation was: it can draw, but it doesn’t understand aesthetics. Now that layer of confidence is starting to crack.

Advanced Prompt Techniques

After running through these 10 test cases, here are some tips for more consistent results:

1. Specify layout first, then content: Write “vertical / horizontal / A3 / infographic” first, then the specific elements. This gives more stable structural results.
2. Use specific style references: Terms like “Kodak Portra 400”, “high-end magazine layout”, “showroom quality” are much more effective than vague words like “beautiful” or “premium”.
3. Explicitly state whitespace and hierarchy: Adding “reasonable whitespace, visually unified, clear information hierarchy” noticeably improves the layout feel.
4. Lock in Chinese text explicitly: Put any text that should appear in quotes, like titling it “Spring Outing”, rather than letting the model make it up.
5. Iterate step by step: Don’t scrap the first result and start over. Use “on this image, change XX to YY” phrasing to trigger local editing.
6. Use the editing panel: The editing panel supports aspect ratio changes, regeneration, and local editing. Often you don’t need to rewrite the prompt—a small tweak is enough.

FAQ

Can free users use ChatGPT Images 2.0?

Yes. Free users can access it, but with daily generation limits—usually single-digit images per day, and you may need to queue during peak hours. It’s fine for casual experimentation; if you want high-frequency generation or multi-version comparisons, you’ll likely exhaust your daily limit.

How many images can I generate per day?

Free users have limited daily quotas (officially adjusted dynamically based on load); paid users get significantly higher limits, sufficient for regular high-frequency use; Pro users basically don’t need to worry about limits, making it ideal for designers, operators, and content creators with heavy image volume.

What if generated Chinese text is blurry or misaligned?

Three quick tips: first, write the exact text you want in the prompt (use quotes); second, specify font styles (Songti, Kaiti, Heiti) instead of letting it improvise; third, use “local editing” in the editing panel to regenerate the text area specifically. GPT-image-2’s Chinese rendering has improved significantly, but occasional manual tweaking may still be needed.

What if generation fails or the prompt exceeds limits?

Three common causes: triggering content safety policies (try rewording), daily quota exhausted (wait for next day’s reset or upgrade), or server peak hours (try again later).

A Note on the Design Industry

The impact of GPT-image-2 on the design industry is bigger than any previous iteration. Because “drawing” itself is no longer a scarce skill.

But drawing is just the execution layer of design. What’s truly scarce is always: can you understand the problem; can you understand the user; can you judge why a layout should be arranged a certain way; can you find the solution that best fits the business, the distribution channel, and the conversion goal.

AI hasn’t fully taken those away yet. The era of execution-heavy design is indeed ending, but the designer’s era isn’t necessarily over—in some ways, it’s just beginning.