Image Generation API

Guide for AI image generation APIs

Nano Banana Pro Group Image Generation Guide: 6 Reference Image Techniques for Multi-Image Consistency

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When creating series illustrations, e-commerce main images, or picture book storyboards, the most frustrating part is never "drawing one good picture," but rather "ensuring the character is still recognizable when drawing the second one." Nano Banana Pro (which is Google's Gemini 3 Pro Image) performs exceptionally well in multi-image consistency, leading to a frequently asked … Read more

In-depth analysis of Nano Banana Pro image generation principles: Inpainting or local modification? The truth behind Pixel-Perfect

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When Google DeepMind released Nano Banana Pro on November 20, 2025, they repeatedly emphasized one point: "untouched areas remain pixel-perfect — no generation drift, no quality loss across iterative edits." If you take this literally, it sounds like the AI has achieved "Photoshop-style true local editing." However, if you understand the architecture of Gemini 3 … Read more

Stable and reliable gpt-image-2 official reverse API: APIYI codex channel 30 sizes integration guide

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If you've just integrated gpt-image-2 into your production environment, you've likely hit a wall with two major issues: rate limits and stability. The official OpenAI rate limit for gpt-image-2 is notoriously strict—Tier 1 accounts are capped at just 5 requests per minute, meaning even light batch processing triggers 429 errors. Plus, when you run into … Read more

Analysis of the gpt-image-2 image layering principle and the 6 key steps for API integration

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Author's Note: This article provides a systematic explanation of the real principles behind gpt-image-2 image layering, the phenomena observed in Python backend processing, API invocation methods, and cost optimization strategies. It aims to help developers avoid the common mistake of confusing toolchain capabilities with native model capabilities. If you've been using gpt-image-2 recently for posters, … Read more

9-Step Practical Guide to Integrating gpt-image-2 with the Official API: From Zero to Production

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Released by OpenAI in April 2026, gpt-image-2 has quickly become the most talked-about model in the image generation space. It boasts 99% character-level text rendering accuracy, 4K high-definition output, native Chinese/CJK support, and integrated O-series reasoning capabilities. However, the first question many developers ask after getting their hands on the model is: How exactly do … Read more

Which is stronger, GPT-Image-2 or Nano Banana 2? An 8-dimensional advantage comparison of text-to-image and image editing

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In the second quarter of 2026, the AI image generation market saw an unprecedented "twin star" landscape emerge: Nano Banana 2 (Gemini 3.1 Flash Image) was released on February 26th, challenging Pro-level quality with Flash-level speed, capable of generating images in just 1-2 seconds. GPT-Image-2 debuted on April 21st, setting a new industry benchmark with … Read more

Xiaohongshu FireRed Image Edit 1.1 In-depth Analysis: 5 Core Capabilities of Open Source Image Editing SOTA

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description: A comprehensive guide to Little Red Book's open-source FireRed Image Edit 1.1, featuring 5 core capabilities, benchmark data, and API integration details. Author's Note: This is a comprehensive breakdown of the open-source FireRed Image Edit 1.1 image editing model from Little Red Book (Xiaohongshu). We’ll cover its 5 core capabilities, benchmark data, technical architecture, … Read more

In-depth Analysis of Meituan LongCat-Image: 4 Key Advantages of a 6B Parameter Model Outperforming an 80B Large Language Model

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Author's Note: A comprehensive analysis of the open-source LongCat-Image image generation and editing model from Meituan. With only 6B parameters, it outperforms several 20B-80B models, provides full rendering support for all 8105 standard Chinese characters, and includes benchmark data and API access details. In the AI image generation world, bigger models usually mean better results. … Read more

Nano Banana Pro model invocation pitfalls: imageConfig determines resolution, do not add size parameter

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Many developers calling the Nano Banana Pro API (which corresponds to the Google gemini-3-pro-image-preview model) for the first time fall into the same trap: they reuse the size: "1024×1024" parameter from the OpenAI / DALL-E era. As a result, the image resolution either refuses to change, the request returns a 400 error, or the parameter … Read more

Does Nano Banana Pro support the Seed parameter? 1 definitive answer + 4 consistency alternatives

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"I passed a seed to Nano Banana Pro, and it threw an error: Invalid value at 'generation_config.seed' (TYPE_INT32). Does it actually support a seed or not?"—this was one of the most frequently asked questions in the Gemini image API community back in 2026. Let’s start with the conclusion: Nano Banana Pro (gemini-3-pro-image-preview) does not support … Read more