Google GemPix: Google JUST CRUSHED EVERY IMAGE MODEL YET! Use it for FREE Now!
Takeaways
- 🚀 Google appears to be testing a new image model called GemPix (also written as Gemix/Gempix) that offers major improvements over existing image models.
- 🔍 Evidence of GemPix was found inside Google's experimental Whisk project and on the public-facing Image FX tool, suggesting cross-product testing.
- 🧩 The Whisk code references three modes (default, genix, and R2I), implying support for reference-image workflows and advanced editing.
- 🖼️ R2I likely stands for "reference-to-image," meaning GemPix will handle reference-based generation and precise edits, not just text-to-image.
- 🧪 GemPix features are being rolled out in stages — first to trusted testers and then more broadly — with UI and API hints already visible.
- 📱 There's talk that a compact "nano" variant (nicknamed Nano Banana) could run locally on Android devices and may debut at an upcoming Pixel event.
- ⚙️ The nano variant reportedly outperforms competitors like Flux Context and OpenAI's GPT Image in the creator's tests, especially for edits.
- 🎨 Real examples shown include: generating a 3D/anime panda-in-New-York, adding a baby panda into an existing scene, converting anime to a sad mood, and re-coloring shoes with PokémonGoogle GemPix details themes — all produced high-quality, coherent results.
- 🧠 The model demonstrates better style-consistency and depth handling (e.g., layering, correct occlusion) compared with some rivals.
- 📈 Larger GemPix variants are likely to be offered via API and could be integrated into Gemini 3.0/Flash-image iterations, according to speculation.
- 📣 The creator recommends trying GemPix on LM Arena where an image option and image-editing with attached references are available for testing.
- 👍 Overall conclusion: GemPix (and its nano version) is presented as a significant step forward in image generation and editing — fast, flexible, and promising for both local Android use and wider API access.
Q & A
What is GemPix (referred to as Gempix or Gemix in the script)?
-GemPix 2 is a cutting-edge model from the Gemini family that can generate images from text and perform reference-based edits. Discover more about this powerful tool at GemPix 2.
Where was evidence of GemPix spotted according to the video script?
-The model was spotted inside Google's Image FX platform and in the code for Whisk, an experimental Google Labs project.
What is Whisk and why does its code matter here?
-Whisk is an experimental Google Labs project used to test AI features. Finding references to GemPix in its code suggests Google is actively testing and integrating the model.
What does the mention of three modes — default, genix, and R2I — imply?
-It implies the model supports multiple modes including a reference-to-image (R2I) mode, which likely enables using reference images for edits or guided generation.
What is R2I likely to stand for and what does it enable?
-R2I likely stands for 'referenceGemPix image model-to-image' and it enables generation or editing of images using one or more supplied reference images for style, layout, or content guidance.
How does GemPix (nano banana) compare to other image models like GPT Image or Flux Context in the script's tests?
-The presenter claims the GemPix 'nano banana' variant outperforms GPT Image and Flux Context in prompt-following, color handling, style consistency, depth, and realistic edits.
What is 'nano banana' in the context of the script?
-'Nano banana' is the reported internal name for a smaller/nano version of GemPix, apparently available for quick testing and said to be very capable despite its size.
What examples did the presenter test to compare models?
-They tested generation of a 3D-anime panda in a New York background, adding a baby panda into an existing scene, making an anime scene look sad, designing Pokémon-colored shoes, and creating a dramatic YouTube thumbnail.
What strengths did GemPix demonstrate in those example edits and generations?
-GemPix followed prompts closely, preserved consistent style between inserted and original elements, produced convincing depth and occlusion, used colors and fabric sections sensibly, and produced cinematic thumbnails.
Where can users try GemPix right now according to the script?
-The speaker says GemPix can be tried on LM Arena by selecting the image option and uploading a reference image or entering a text prompt.
Is GemPix expected to be released more widely or tied to hardware events?
-The script suggests Google may roll it out in stages—first to trusted testers, then publicly—and possibly announce or demo it around a Pixel hardware event.
Will GemPix only run in the cloud or also locally on devices?
-The script mentions that the nano variant might run locally on Android devices (e.g., Pixel phones), while larger variants would likely be available via API or cloud.
How might GemPix relate to Gemini 3.0 or previous Gemini image models?
-The presenter speculates GemPix could be part of a Gemini 3.0 'flash' image capability, following previous Gemini 2.0 flash image models, integrating image generation/editing into the broader Gemini family.
What limitations or caveats did the presenter note about the discovery?
-The presenter notes evidence is from code and staged tests, so rollout appears gradual; some claims are based on early tester experiences and observations rather than a formal public announcement.
What should a user do if they want to evaluate GemPix themselves?
-Follow the script's suggestion: visit LM Arena's image option to test generation and image editing with prompts and reference images, and watch for official Google announcements tied to events like Pixel launches.
Outlines
- 00:00
🎨 Google’s new Gemini image model (Gempix/Gemix) — reference-based generation & editing
This paragraph explains that Google appears to be developing a new Gemini image model referred to as Gempix/Gemix (also mentioned as GEMPIX) and that parts of it are already discoverable in public-facing projects. The speaker notes evidence found in Google’s experimental Whisk project and Image FX tool—code references revealing three modes (default, genix, and an R2I mode that likely means “reference-to-image”), plus API/UI hints—suggesting the model supports reference-image workflows. The paragraph highlights that this would allow not only text-to-image generation but precise, reference-based editing and remixing (similar in concept to tools like MidJourney’s describe or Stable Diffusion’s ControlNet) directly inside Google’s ecosystem. It summarizes observations that Google may be doing a staged rollout (trusted testers first, then wider public), that these features appear across Whisk and Image FX (hinting at a coordinated launch), and speculates about tying the announcement to an upcoming Pixel/hardware event. The author compares the new model to previous Gemini “flash” image models and OpenAI’s GPT image model, emphasizing that it can both generate from scratch and edit images via naturalGoogle Gemini image model-language prompts. They also mention LM Arena as a place where the model can already be tried (image option, attach an image for edits or generate from prompts) and report a rumored “nano banana” variant—described as a smaller on-device (nano) version of GEMPIX—that reportedly outperforms other compact models (e.g., Flux Context, GPT Image). The overall tone is excited and frames GEMPIX/Gemix as a significant step toward integrated, flexible image creation and editing within Google’s products.
- 05:01
🧪 Hands-on examples & comparisons — Nano Banana wins on edits, depth, and coherence
This paragraph walks through hands-on tests and visual comparisons the speaker performed using the nano variant (nicknamed “Nano Banana”) against other image models (referred to as GPT Image and Flux Context). Multiple examples are described: a prompt asking for a 3D/anime-styled panda on a tower in New York (where GPT Image produced a flatter, hand-drawn result with fewer colors, while Gemix/Nano Banana produced a brighter, prompt-faithful 3D-like image); an edit task inserting a baby panda into an existing scene (Nano Banana matched the scene’s style and depth—placing the new panda correctly in front of Pikachu’s tail—where Flux Context performed poorly); an anime scene converted to a sad mood (Nano Banana produced a convincing, cinematic anime-frame result while Flux Context did not); and a shoe redesign task applying Pokémon-inspired colors (both performed, but Nano Banana reportedly handled fabric-section colors more logically, producing a potentially manufacturable design). The speaker also used an image-to-thumbnail edit request—asking for a dramatic, documentary-style YouTube thumbnail—and found Nano Banana produced more cinematic, coherent results than Flux Context. The paragraph relays community chatter that the nano model may run locally on Android and could be launched at an imminent Pixel event (the speaker says ~3 days from now), with larger variants likely available later via API—possibly integrated into a future Gemini 3.0 flash release. The paragraph closes by encouraging viewers to try the model on LM Arena, share thoughts, and subscribe, reiterating the speaker’s enthusiasm for the model’s editing and generation quality.
Mindmap
Keywords
💡GemPix
GemPix is an advanced image generation model developed by Google, which is capable of both generating images from scratch and editing existing images. It is part of Google's Gemini series and is reportedly much more powerful than previous models, such as GPT's image models. In the video, the speaker highlights how GemPix's nano version, named 'Nano Banana,' produces images with better style coherence, depth, and color accuracy than models like Flux Context.
💡Google Labs
Google Labs is an experimental platform where Google tests out new AI features before they become mainstream. The speaker refers to this as a place where Google tries out cutting-edge tools, including the new GemPix model, before making them available to the wider public. This allows Google to refine features based on user feedback.
💡Whisk
Whisk is a Google Labs project where experimental AI tools are first introduced. In this video, the speaker notes that the GemPix model was discovered within the code of Whisk, signaling its early testing phase. Whisk plays a critical role in Google'sGoogle GemPix details strategy for testing new technologies, allowing them to iron out potential issues before a full release.
💡R2I (Reference to Image)
R2I stands for 'Reference to Image,' which is a mode in the GemPix model that enables users to use an existing image as a reference to guide image generation or editing. This is a significant feature because it suggests that Google’s new model will allow for precise editing or remixing of images, improving the workflow for those who want to make specific alterations based on reference images.
💡Nano Banana
Nano Banana is the name of the nano version of the GemPix image generation model. The speaker compares it to other leading models like Flux Context and GPT's image models, emphasizing that even this smaller version of GemPix outperforms them by a considerable margin in terms of image quality, accuracy, and style coherence. Nano Banana is positioned as a tool that could be available on Android devices soon, especially tied to Google's Pixel event.
💡AI Image Editing
AI image editing refers to the use of artificial intelligence to modify or enhance digital images. In this video, the speaker demonstrates how GemPix’s advanced editing capabilities can generate new elements or adjust existing images based on user prompts. For example, adding a baby panda into an existing scene is a form of AI image editing, where the model integrates the new element seamlessly with the rest of the image.
💡Image FX
Image FX is a public-facing platform by Google that allows users to experiment with image generation models. According to the video, GemPix is being tested on Image FX, where users can see improved output styles and better image quality. The speaker mentions that evidence from the platform supports the idea that GemPix is being rolled out to a select group of users for further testing.
💡Flux Context
Flux Context is another image generation model mentioned in the video as a comparison to GemPix. The speaker highlights how Flux Context produces less accurate or stylistically coherent images when compared to GemPix, especially when editing or generating more complex scenes. The comparison emphasizes how much better GemPix performs in terms of depth, style, and color accuracy.
💡GPT Image Model
The GPT image model refers to OpenAI's image generation technology, which is based on the GPT architecture. This model is capable of generating images from text prompts, similar to how GPT models generate text. In the video, the speaker contrasts GPT’s image model with GemPix, noting that while GPT can generate images from text, GemPix's advanced features, like editing and reference-based generation, give it an edge over GPT.
💡Pixel Event
The Pixel event is an annual hardware launch event hosted by Google, where new devices, such as the Pixel phone, are introduced. The speaker speculates that Google might tie the public release of the GemPix model to the upcoming Pixel event, as has been the pattern with previous AI releases, where AI technologies are often launched alongside new Pixel devices. This suggests that GemPix could be available on Android devices soon after the event.
Highlights
Google's new Gemini image model, 'GemPix,' is set to revolutionize image generation and editing with advanced AI features.
GemPix is available now on Google's Image FX platform, as well as in the experimental Whisk Labs project.
The new model offers three modes: default, Genix, and an advanced mode called R2I (Reference to Image).
GemPix allows users to both generate images from scratch and edit or remix images with reference inputs.
Google's integration of advanced image editing tools directly into its ecosystem makes it more versatile than ever before.
Early tests reveal improved image quality and more refined outputs compared to previous models, including GPT's image model.
GemPix is being rolled out gradually, starting with trusted testers and soon to be available to the wider public.
The model shows great potential for both creative image generation and precise image editing using natural language prompts.
One notable feature is the 'Nano Banana' model, a lighter version of GemPixJSON code correction that already outperforms competitors like Flux Context.
Examples of generated images show GemPix's ability to follow complex prompts, like creating a panda on a New York tower in anime style.
GemPix excels at creating depth in images, as demonstrated by the accurate rendering of a baby panda in a scene with Pikachu.
The Nano Banana model also outperforms in tasks like generating a sad anime character, capturing the scene's tone accurately.
GemPix's ability to edit images, such as creating a special edition shoe with Pokémon colors, shows its impressive flexibility.
The model also shines in turning ordinary images into cinematic YouTube thumbnails with a dramatic and engaging look.
GemPix's potential to be launched alongside Google's upcoming Pixel event suggests it will be integrated into Android devices for local use.