Is GPT-Image-1.5 competitive with Nano Banana?
Image generation has shifted from an experimental novelty to a tool teams rely on in production workflows. Designers use it for early-stage visual exploration and design. Educators use it to support visual explanations of complex concepts. Developers rely on it to generate assets, mock interfaces, and produce structured visuals such as diagrams and infographics.
While competitors iterated rapidly, especially in terms of speed, editing, and identity consistency, OpenAI’s image story seemed quiet. With GPT-Image-1.5, OpenAI is signaling a deliberate return to the image generation space, one that is focused less on spectacle and more on control, precision, and real-world workflows.
This newsletter examines what GPT-Image-1.5 offers and evaluates it in practice against a commonly cited alternative, Gemini Nano Banana.
What OpenAI released with GPT-Image-1.5#
OpenAI officially introduced GPT-Image-1.5 on December 16, 2025, as the model powering the new ChatGPT images experience, with the same capabilities also exposed through the OpenAI API. Rather than presenting it as a standalone feature, OpenAI positioned this release as a foundational upgrade to how ChatGPT generates and edits images.
At a high level, GPT-Image-1.5 focuses on a small set of practical improvements that directly address how teams use image generation today:
Stronger instruction adherence allows longer and more specific prompts to be followed with fewer unintended changes.
High-fidelity image editing, where only the requested elements are modified while lighting, composition, and subject identity are preserved.
Improved text rendering and layout, making it more suitable for diagrams, infographics, and structured visuals.
Faster generation and lower iteration cost, enabling more experimentation without long wait times.
Taken together, these changes indicate a shift in how OpenAI approaches image generation. GPT-Image-1.5 prioritizes predictable behavior within real workflows over producing striking images in isolation. The emphasis on precision, editability, and consistency suggests an optimization for teams that need assets they can refine, reuse, and trust, not just visuals that appear visually appealing at first glance.
