
DeepSeek Just Dropped TERMINUS: The Next Level Hybrid Model
September 24, 2025
China’s Seedream 4.0 Just Outperformed Google’s Nano Banana (And It’s Open Source)
September 25, 2025
Today, we’re joined by Oliver Wang, principal scientist at Google DeepMind and tech lead for Gemini 2.5 Flash Image—better known by its code name, “Nano Banana.” We dive into the development and capabilities of this newly released frontier vision-language model, beginning with the broader shift from specialized image generators to general-purpose multimodal agents that can use both visual and textual data for a variety of tasks. Oliver explains how Nano Banana can generate and iteratively edit images while maintaining consistency, and how its integration with Gemini’s world knowledge expands creative and practical use cases. We discuss the tension between aesthetics and accuracy, the relative maturity of image models compared to text-based LLMs, and scaling as a driver of progress. Oliver also shares surprising emergent behaviors, the challenges of evaluating vision-language models, and the risks of training on AI-generated data. Finally, we look ahead to interactive world models and VLMs that may one day “think” and “reason” in images.
For the full list of resources for this episode, visit the show notes page: https://twimlai.com/go/748.
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📖 CHAPTERS
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00:00 – Introduction
4:39 – Nano banana
5:35 – Nano banana vs Imagen and trajectory of image generation models
7:01 – Integration of Nano banana in Gemini
9:52 – Nano banana— a general purpose model
13:42 – Model consistency and editing capabilities
15:41 – Data quality and model architecture
18:13 – Use cases
24:10 – One-shot models vs. node-based interfaces
28:33 – Fine-tuning
30:32 – Exciting trends in image generation and VLMs
32:40 – Overcoming the challenges of model quality
34:36 – Model evaluation challenges
36:32 – Nano banana pros and cons
38:58 – Prompt rewriting
40:36 – Papers
41:52 – Accessibility of the research
46:45 – Verifiable domains
49:49 – Tension between accuracy and aesthetics
52:50 – Narrow data distribution in image generation
55:15 – AI-generated images for training data
57:56 – Model scale versus data curation
58:55 – Maturity of text versus image domains
🔗 LINKS & RESOURCES
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Nano Banana: Image editing in Google Gemini just got a major upgrade – https://blog.google/products/gemini/updated-image-editing-model/
Google Gemini’s AI image model gets a ‘bananas’ upgrade – https://techcrunch.com/2025/08/26/google-geminis-ai-image-model-gets-a-bananas-upgrade/
Gemini Flash – https://deepmind.google/models/gemini/flash/
Genie 3: A New Frontier for World Models – 743 – https://twimlai.com/podcast/twimlai/genie-3-a-new-frontier-for-world-models/
Google I/O 2025 Special Edition – 733 – https://twimlai.com/podcast/twimlai/google-i-o-2025-special-edition/
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