Google's advanced AI-powered video-to-image generation model, designed to generate high-quality static images from video clips combined with text instructions.
Nano Banana 2 — คุณภาพระดับ Pro ความเร็วระดับ Flash
V2
หรือที่รู้จักในชื่อ Gemini 3.1 Flash Image
โมเดลภาพล่าสุดจาก Google DeepMind ที่ผสมผสานความสามารถขั้นสูงของ Nano Banana Pro เข้ากับความเร็วของ Gemini Flash — สร้างภาพเร็วขึ้น 3-5 เท่า รองรับความละเอียดสูงสุด 4K และรักษาความสม่ำเสมอของตัวละครได้ถึง 5 ตัวในเวิร์กโฟลว์เดียว
Explore curated prompt templates showcasing Nano Banana 2's key capabilities — text rendering, character consistency, search grounding, and 4K output.
Text Rendering
Marketing Mockup with Text
Generate marketing visuals with accurate, legible text — one of NB2's standout improvements
Prompt
A minimalist coffee shop promotional poster with the text 'MORNING BREW — Fresh Roasted Daily' in elegant serif font, warm earth tones, steam rising from a ceramic cup, clean layout with plenty of whitespace
Character Consistency
Multi-Scene Character
Maintain character consistency across multiple scenes — supports up to 5 characters per workflow
Prompt
A young woman with short red hair and freckles, wearing a green jacket, standing in a rainy Tokyo street at night with neon reflections on wet pavement, cinematic lighting, photorealistic
Photo to Action Figure
Person to Action Figure
Transform people from photos into collectible action figures with custom packaging
Prompt
Transform the person in the photo into an action figure, styled after [CHARACTER_NAME] from [SOURCE / CONTEXT]. Next to the figure, display the accessories including [ITEM_1], [ITEM_2], and [ITEM_3]. On the top of the toy box, write "[BOX_LABEL_TOP]", and underneath it, "[BOX_LABEL_BOTTOM]". Place the box in a [BACKGROUND_SETTING] environment.
Search Grounding
Real-World Reference Generation
Leverage Image Search Grounding to generate accurate real-world subjects like landmarks and brands
Prompt
A photorealistic aerial view of the Eiffel Tower at golden hour, with the Seine River winding through Paris below, warm sunset light casting long shadows, high detail, 4K resolution
Product Photography
Product Design Render
Create professional product photography with precise control over lighting and composition
Prompt
A frosted glass perfume bottle with a marble cap on a white marble surface, soft studio lighting from the left, subtle reflections, minimalist luxury aesthetic, product photography style
Style Transfer
Artistic Style Transformation
Apply diverse artistic styles while maintaining subject integrity
Prompt
Transform this photo into Studio Ghibli animation style, keeping the same composition and subjects, lush watercolor backgrounds, soft diffused lighting, whimsical atmosphere
4K Output
Ultra High Resolution Scene
Generate detailed scenes at up to 4K resolution with rich textures
Prompt
A cozy Japanese ramen shop interior at night, steam rising from bowls, warm amber lighting, detailed wooden counter with various condiments, a chef working in the background, 4K, ultra detailed
กรณีการใช้งาน
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ถ่ายภาพสินค้า
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ม็อกอัพการตลาด
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เนื้อหาโซเชียลมีเดีย
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ออกแบบข้อความซ้อนทับ
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ออกแบบตัวละคร
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แก้ไขและรีทัชภาพ
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เนื้อหาภาพแบรนด์
ทำไมต้องเลือก Nano Banana 2?
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ความเร็วระดับ Flash
เร็วกว่า Nano Banana Pro 3-5 เท่า ใช้เวลาสร้างภาพมาตรฐานเพียง 4-8 วินาที
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ค่าใช้จ่ายประมาณครึ่งหนึ่งของ Nano Banana Pro — ทำให้การสร้างภาพ AI คุณภาพสูงเข้าถึงได้ง่ายขึ้น
การเข้าถึง API:Gemini API, Vertex AI, AI Studio, Gemini CLI
สัมผัส Nano Banana 2
สร้างภาพระดับ Pro ด้วยความเร็ว Flash — สร้างภาพสวยงามพร้อมความสม่ำเสมอของตัวละคร การแสดงผลข้อความ และรองรับความละเอียด 4K
✨เครดิตฟรีเพื่อเริ่มต้น
⚡เข้าถึง API ทันที
🌐ไม่ต้องตั้งค่าใดๆ
Google Nano Banana 2 Reference to Image
Nano Banana 2 Reference to Image (Gemini 3.1 Flash Image) is Google's advanced AI-powered video-to-image generation model, designed to generate high-quality static images from video clips combined with text instructions. Built on the same cutting-edge model as Nano Banana 2 Edit, it adds the ability to use video content as a rich reference source — extracting visual context, themes, and key frames to synthesize new images with precision and semantic awareness.
This model is ideal for creating thumbnails, posters, promotional artwork, and scene summaries by leveraging the visual richness of existing video content alongside natural language guidance.
Why Choose This?
Video as reference — Provide a video clip (HTTP URL or YouTube URL) and let the model extract its visual context to guide image generation.
Multi-image reference — Optionally upload up to 10 additional reference images to complement the video input for complex compositions.
Natural language control — Describe exactly what you want with a text prompt; the model understands context, themes, and relationships from both the video and text.
Thinking levels — Choose how much internal reasoning the model applies — higher thinking levels improve quality on complex tasks.
Media resolution control — Balance detail and token usage for input video frames with LOW, MEDIUM, or HIGH media resolution modes.
Web & image search grounding — Optionally enable real-time web or image search to enrich generation with current information.
Multi-resolution output — Generate at 1K, 2K, or 4K resolution.
Flexible aspect ratios — Multiple options including 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, and 21:9.
Format choice — Export in PNG or JPEG format.
How It Works
The model analyzes your video clip by sampling frames at the specified FPS rate, then interprets the visual content within its multimodal context window. Combined with your text prompt and any additional reference images, it synthesizes a new image grounded in the video's themes, style, and key visual elements. This makes it especially powerful for creating content that is visually consistent with existing video assets.
Parameters
Core Inputs
Parameter
Required
Description
prompt
Yes
Text description of the desired output image
video_clips
Yes
Source video clip(s) for reference generation (max: 1, see below)
Reasoning depth: default, high, minimal. Higher levels improve quality on complex tasks but increase latency.
media_resolution
No
How input media frames are processed: default, low, medium, high. LOW reduces tokens per frame, allowing longer videos.
enable_web_search
No
If enabled, grounds generation with real-time web information.
enable_image_search
No
If enabled, grounds generation with real-time image search results.
How to Use
Provide a video clip — enter the video URL (HTTP or YouTube) and set start/end times and FPS sampling rate.
Write your prompt — describe the output image clearly (e.g., "Create a cinematic poster based on the key scenes in this video").
Add reference images (optional) — upload additional images to guide composition or style.
Choose aspect ratio (optional) — select a preset or leave empty for default.
Select resolution — choose 1K, 2K, or 4K based on your quality needs.
Choose output format — PNG for transparency support, JPEG for smaller file size.
Adjust advanced settings (optional) — set thinking level, media resolution, or enable search grounding.
Run — submit and download your generated image.
Pricing
The total cost is determined by the output image resolution multiplied by the number of output images, plus optional per-request fees for video clip input, web search, and image search grounding.
The video clip fee (0.07),websearchfee(0.014), and image search fee ($0.014) are each charged once per request when the respective feature is enabled, regardless of content volume.
Best Use Cases
Video Thumbnail Generation — Automatically create compelling thumbnails that reflect the video's content and mood.
Promotional Posters — Generate movie-style or campaign posters grounded in actual video footage.
Scene Summarization Art — Create visual summaries or highlight artwork from long-form video content.
Brand Content Creation — Produce consistent image assets from brand video campaigns.
Educational Infographics — Transform instructional videos into static visual materials.
Social Media Assets — Generate platform-optimized images (vertical, square, landscape) from video content.
Pro Tips
Use low FPS (0.5–1) for long videos to keep token usage within limits while still capturing key frames.
Set precise start/end times to focus the model on the most relevant segment of your video.
Combine specific text prompts with the video input — vague prompts may produce generic results.
Add reference images alongside the video to guide composition style more precisely.
Use thinking_level: high for complex scene interpretations or when visual fidelity matters most.
Set media_resolution: low when analyzing long videos to allow more frames within the context window.
2K offers excellent quality at a reasonable price — only $0.04 more than 1K per image.
YouTube URLs are supported directly — no need to download and re-upload public videos.
Notes
Both prompt and video_clips are required fields.
Maximum video clips: 1 per request.
HTTP video URLs are limited to 15MB; use YouTube URLs for larger videos.
Maximum additional reference images: 10.
FPS range: 0–24. Higher FPS captures more frames but consumes more tokens.
The video clip fee ($0.07) is a flat per-request charge, not per frame or per second.
If aspect_ratio is not selected, the model uses a default ratio.
4K resolution costs 2× the standard 1K rate.
Ensure your content and prompts comply with Google's Safety Guidelines.
Related Models
Nano Banana 2 Edit — Edit images using text prompts and reference images (no video input).