Modèles de génération d’images
Classement des modèles mis à jour à partir de données d’utilisation réelles.
Les modèles sont classés selon le nombre total de jetons de prompt et de réponse traités via l’API OpenRouter au cours des 7 derniers jours. Affichage des 12 meilleurs modèles. Les classements mesurent l’utilisation sur OpenRouter et reflètent l’adoption, et non la qualité des modèles ou leurs performances aux tests de référence.
Les modèles de génération d’images créent des images à partir de prompts textuels, et la plupart acceptent également des images de référence. Les modèles de l’API d’images reçoivent un prompt via POST /api/v1/images et renvoient l’image dans la réponse. D’autres génèrent des images via Chat Completions. Les meilleurs modèles actuels sont Nano Banana 2 (Gemini 3.1 Flash Image), GPT Image 2.5 Sunburst et Nano Banana 2.1. La tarification est par image, mégapixel ou jeton selon le modèle. Appelez GET /api/v1/images/models pour connaître les modèles disponibles via l’API d’images ainsi que les résolutions et les rapports d’aspect qu’ils prennent en charge, et consultez le guide de génération d’images pour le format des requêtes.
Modèles de génération d’images sur OpenRouter
Google: Nano Banana 2 (Gemini 3.1 Flash Image)
5,84B jetons
Gemini 3.1 Flash Image, a.k.a. "Nano Banana 2," is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced contextual understanding with fast, cost-efficient inference, making complex image generation and iterative edits significantly more accessible. Aspect ratios can be controlled with the image_config API Parameter
OpenAI: GPT Image 2.5 Sunburst
4,07B jetons
GPT Image 2.5 Sunburst is an image generation and editing model from OpenAI, positioned as the precision-oriented tier of the GPT Image 2.5 series. It is suited to detailed creative work where editing accuracy matters more than generation speed, via the dedicated Images API.
Google: Nano Banana 2.1
3,77B jetons
Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product recontextualization, mask- and ink-based editing, and factual accuracy, and renders photorealistic skin tones, detailed materials, lighting, and coherent backgrounds. It accepts text and image inputs, returns images with optional text, and supports 1K, 2K, and 4K output plus extended aspect ratios via the image_config API Parameter.
ByteDance Seed: Seedream 5.0 Flash
2,52B jetons
Seedream 5.0 Flash is an image generation and editing model from ByteDance Seed. It is the fast, cost-efficient tier of the Seedream 5.0 family, suited for high-volume production and interactive editing workflows that need precise edits at low latency.
OpenAI: GPT Image 2.5 Flare
1,75B jetons
GPT Image 2.5 Flare is an image generation and editing model from OpenAI, positioned as the speed-oriented tier of the GPT Image 2.5 series. It is suited to high-volume everyday generation, creator content, and rapid prototyping via the dedicated Images API.
Meta: Muse Image
1,64B jetons
Muse Image is an agentic image generation model from Meta that generates and edits images from text and reference images. Unlike single-pass image models, it reasons before it renders, breaking down multi-part prompts and refining its output within the chain of thought, and invokes web search for factual accuracy on knowledge-intensive prompts.
The model supports text-to-image generation, targeted image editing, multi-image composition, reference-image conditioning for style and subject consistency across a series, and precise text rendering within generated images. Iterative editing works by passing the previous output image back with a new instruction.
Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is Google's fastest, most cost-efficient Gemini image model, built for high-velocity developer pipelines and rapid-fire visual exploration. It delivers text-to-image generation in roughly 4 seconds — about 2.7× faster than Gemini 3.1 Flash Image — while keeping the character consistency, precise editing, and real-world knowledge of the Nano Banana family.
A single drop-in API handles text-to-image, image editing, and multi-image composition. As a multimodal model it also returns text alongside images. Outputs are generated at 1K resolution across 14 aspect ratios and carry an invisible SynthID watermark so they can be identified as AI-generated.
Positioned as the best balance of quality and speed in the Nano Banana 2 line, it lets you generate thousands of images at a fraction of the cost of heavier production models — ideal for prototyping, real-time apps, and visual workflows at scale.
Tencent: Hy Image 3.5 Preview
1,57B jetons
Hy Image 3.5 Preview is a unified image generation and editing model from Tencent. It handles text-to-image, image-to-image, and multi-turn editing through one endpoint, taking up to 20 reference images per request and producing output up to 4K. Built on the 80B mixture-of-experts Hy Image 3.0 base, it is particularly strong at subject consistency across edits, prompt-faithful composition, and rendering Chinese and English text inside images.
Google: Nano Banana (Gemini 2.5 Flash Image)
1,57B jetons
Gemini 2.5 Flash Image, a.k.a. "Nano Banana," is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image generation, edits, and multi-turn conversations. Aspect ratios can be controlled with the image_config API Parameter
OpenAI: GPT Image 2
1,41B jetons
OpenAI's latest image generation model. Supports high-fidelity image generation and editing via the dedicated Images API.
OpenAI: GPT-5.4 Image 2
1,36B jetons
GPT-5.4 Image 2 combines OpenAI's GPT-5.4 model with state-of-the-art image generation capabilities from GPT Image 2. It enables rich multimodal workflows, allowing users to seamlessly move between reasoning, coding, and visual generation within the same interaction.
Google: Nano Banana Pro (Gemini 3 Pro Image)
1,31B jetons
Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and high-fidelity visual synthesis. The model generates context-rich graphics, from infographics and diagrams to cinematic composites, and can incorporate real-time information via Search grounding.
It offers industry-leading text rendering in images (including long passages and multilingual layouts), consistent multi-image blending, and accurate identity preservation across up to five subjects. Nano Banana Pro adds fine-grained creative controls such as localized edits, lighting and focus adjustments, camera transformations, and support for 2K/4K outputs and flexible aspect ratios. It is designed for professional-grade design, product visualization, storyboarding, and complex multi-element compositions while remaining efficient for general image creation workflows.
Questions fréquentes
Send POST /api/v1/images with the model slug and your prompt. The response returns the image as base64 in data[].b64_json; media_type identifies its format when known, and usage.cost reports the request cost when available. Models that are not on the Image API return images through chat completions instead. The image generation guide covers the full request format.
Listings with published pricing show their price in the unit the provider bills: per image, per megapixel, or per token, and some models price resolution tiers such as 2K and 4K separately. Completed generations are billed for the full image output, so compare prices in the same unit before you choose.
Yes. Pass reference images in input_references as HTTP(S) URLs or base64 data URLs to guide generation from an existing image. Models that accept image input list image in their input_modalities, and the number of references accepted varies by provider.
Call GET /api/v1/images/models for the Image API catalog, then append /endpoints to a model's path (GET /api/v1/images/models/author/slug/endpoints) for each endpoint's resolution tiers, aspect ratios, and pricing lines. In the request, set resolution and aspect_ratio, or the size shorthand. Providers clamp aspect_ratio to the ratios they support, but explicit pixel sizes are provider-dependent: some providers reject them, so check the model's supported_parameters first.
No. One OpenRouter API key works for every image model on this page and for every other model on OpenRouter. Create a key on your API keys page.