kling/kling-v3-omni-image

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单位: $/img

相关模型

• kling/kling-v3-t2i: [Core Function] Kling V3 T2I is the flagship text-to-image generation model. [Strengths] It delivers state-of-the-art aesthetic quality, high-resolution outputs (up to 2K), and exceptional prompt adherence. [Best For] Highly recommended for: professional concept art, photorealistic portraits, and high-fidelity image generation. [Limitations] Do NOT use this model if you need to strictly reference or edit an existing image. [Routing] Use this as the default model for all text-to-image requests on the Kling platform.
• kling/kling-v3-t2v: [Core Function] Kling V3 T2V is the next-generation text-to-video base model. [Strengths] It natively supports generating ultra-long 15-second videos, 4K resolution, and synchronized native audio directly from text. [Best For] Highly recommended for: high-end cinematic creation, 4K video generation, and creating long-form scenes with integrated sound. [Limitations] Do NOT use this model if you need complex multi-shot narratives or deep physics reasoning; use V3 Omni or Video O1 respectively. [Routing] Use this model by default for high-quality text-to-video tasks that require up to 15 seconds, 4K resolution, or native audio without reference images.
• kling/kling-v3-i2i: [Core Function] Kling V3 I2I is the flagship image-to-image editing model. [Strengths] It provides high-quality style transfer and image modification up to 2K resolution based on a reference image. [Best For] Highly recommended for: high-res style transfer and general image editing. [Limitations] Do NOT use this model for complex multi-element fusion (use Omni Image instead). [Routing] Use this by default for standard image-to-image tasks.
• kling/kling-v3-i2v: [Core Function] Kling V3 I2V is the next-generation image-to-video model. [Strengths] It transforms static images into video with support for 4K resolution, 15-second durations, and native audio, providing superior motion and character expressiveness. [Best For] Highly recommended for: animating concept art, bringing portraits to life in 4K, and generating long 15s scenes from a single frame. [Limitations] Do NOT use this model if you need multimodal reference elements (like character consistency across shots) or multi-shot generation; use V3 Omni instead. [Routing] Use this model by default for high-quality single-image-to-video tasks.
• kling/kling-v3-omni-video: [Core Function] Kling V3 Omni Video is the flagship unified multimodal video generation endpoint. [Strengths] It supports multi-shot narratives (up to 6 shots), 15-second durations, native audio, video editing (via refer_type ‘base’), and character/element consistency across shots using <image_N> syntax. [Best For] Highly recommended for: professional video orchestration, multi-shot cinematic sequences, and maintaining strict character consistency. [Limitations] Do NOT use this model for simple, single-shot T2V/I2V tasks where the standard V3 model is more straightforward and cheaper. [Routing] Use this model whenever the user requests ‘multi-shot’, ‘consistent characters’, ‘video editing’, or complex multimodal inputs.
• alibaba/wan2.7-image-pro-edit: [Core Function] Wan 2.7 Image Pro Edit is Alibaba’s flagship reasoning-enhanced image editing model. [Strengths] It supports interactive editing, character-consistent multi-image generation, and complex multi-reference modifications with deep reasoning. [Best For] Highly recommended for: professional image retouching, consistent character sheets, and complex structural edits. [Limitations] Do NOT use this model if you specifically need to use negative prompts to exclude elements during editing (use Qwen Image 2.0 Pro Edit instead). [Routing] Use this by default for high-end image editing and multi-reference consistent character generation.
• openai/gpt-image-2-edit: [Core Function] GPT Image 2 Edit is a high-resolution image-to-image editing model. [Strengths] It excels at making high-fidelity edits and style transformations to a single source image based on a text prompt, preserving details at up to 4K resolutions. [Best For] Highly recommended for: professional photo retouching, upscaling style transfers, and modifying high-resolution concept art. [Limitations] Do NOT use this model for multi-image merging (it only accepts one input image). Do NOT use if you need precise input fidelity control or transparent backgrounds. [Routing] Use this model by default when the user wants to edit a single image and prioritize output resolution/quality. If they need to merge multiple images or control the strictness of the edit (fidelity), use GPT Image 1.5 Edit.
• bytedance/seedream-5.0-lite-edit: [Core Function] Seedream 5.0 Lite Edit is a reasoning-enhanced, smart image editing model. [Strengths] It features superior cross-modal understanding and reasoning, allowing for highly accurate, interactive multi-turn image editing with real-time knowledge enhancement. [Best For] Highly recommended for: complex image editing tasks, structural modifications, and edits requiring deep semantic understanding. [Limitations] As a ‘Lite’ model, raw visual rendering might not match the 4.5 tier. [Routing] Use this model by default for complex, reasoning-based image editing tasks.
• alibaba/qwen-image-2.0-pro-edit: [Core Function] Qwen Image 2.0 Pro Edit is a highly controllable professional image editing model. [Strengths] It seamlessly unifies generation and editing, supporting NEGATIVE prompts during the editing process to strictly exclude elements. [Best For] Highly recommended for: precise image editing where specific elements must be removed or avoided. [Limitations] Does not feature the explicit ‘Thinking Mode’ reasoning of Wan 2.7. [Routing] Route to this model specifically when the user wants to edit an image AND provides a ‘negative prompt’ to exclude elements.
• minimax/minimax-image-01-i2i: [Core Function] MiniMax Image-01 I2I is an image-to-image editing and variation model. [Strengths] It excels at generating new images based on a text prompt while structurally referencing one or more input images. [Best For] Highly recommended for: style transfer, generating variations of existing artwork, and structurally guided image creation. [Limitations] Do NOT use this model if you want to generate video or if you do not have a reference image. [Routing] Use this model when the user provides a reference image and a text prompt to generate a new image.