As of October 2026 the models that follow prompts most accurately are Nano Banana Pro (Google), GPT Image 2 (OpenAI) and FLUX.2 [max] (Black Forest Labs), virtually tied at the top of the prompt adherence rankings. For a brand, though, the real question isn't only "which model executes the text best": it's which process gives you back the real product, identical, in every image. This guide covers what prompt adherence means, how it is measured, which model to use for which job, and how to write prompts that actually get followed.
The short answer: which model follows prompts best
On Lumenfall's prompt adherence leaderboard (updated 28 July 2026) the top spot goes to Google's Nano Banana Pro, followed by OpenAI's GPT Image 2 and Black Forest Labs' FLUX.2 [max], with near-identical scores (1283 vs 1277 and 1277). Nano Banana 2 is fourth. In the general arena-style rankings, OpenAI's GPT Image family is on top instead: at the end of October 2026 the #1 spot on the Artificial Analysis text-to-image leaderboard belongs to GPT Image 2.5, with positions and scores changing at every snapshot.
In practice, the gap between the top three is too small to decide anything. What makes the difference is the kind of image you need, whether you can work from reference images, and how much control you keep after generation.
What prompt adherence is
Prompt adherence measures how closely a generated image matches what the prompt says: the number of objects, the color assigned to each, relative positions ("left of", "behind"), actions, style and requested details. A model with strong prompt adherence doesn't interpret: it executes.
It's a different quality from photorealism or aesthetics. A model can produce beautiful images while ignoring half the instructions, and another can follow all of them with a visually flat result. That's why serious comparisons score the two separately.
How it's measured: arenas and their limits
The most cited rankings work as arenas: users see two images generated from the same prompt by two anonymous models and vote for the better one. The votes produce an Elo-style score. Arenas dedicated to prompt adherence ask voters which image follows the instructions better, not which one they like more.
- Close scores aren't real differences. A few points apart is within the statistical margin.
- Generic prompts. Arena prompts rarely look like a campaign brief built around a specific product.
- Different snapshots. Different arenas on different dates give different rankings, which is why the GPT Image models are first in some and second in others.
- No arena measures fidelity to your product. A model can follow the prompt perfectly and still get your bottle cap wrong.
Quick comparison of the most accurate models
| Model | Developer | Prompt adherence | Where it shines |
|---|---|---|---|
| Nano Banana Pro | #1 on Lumenfall (Jul 2026) | Complex instructions, editing with reference images | |
| GPT Image 2 | OpenAI | #2 on Lumenfall, leads several general arenas | Busy scenes, text and multi-element compositions |
| FLUX.2 [max] | Black Forest Labs | #3 on Lumenfall | Photorealism and adherence; open-weights variants exist (FLUX.2 dev) |
| Nano Banana 2 | #4 on Lumenfall | Lighter option in the Nano Banana family | |
| Seedream 5.0 Lite | ByteDance | #14 on Lumenfall | High visual quality; further behind on this criterion |
| Ideogram | Ideogram | Not its headline strength | Legible text and typography in images |
| Midjourney | Midjourney | Interprets rather than executes | Aesthetics, mood, editorial images |
Positions from Lumenfall's prompt adherence leaderboard as of 28 July 2026 (source). The notes on Ideogram and Midjourney follow our comparison Midjourney vs Flux vs Ideogram.
Which model to use for brand and product work
Packshots and e-commerce images
You need precision, clean backgrounds and correct proportions: the models leading on prompt adherence, used with real product photos as references, are the most solid starting point.
Lifestyle scenes and campaigns
Light, mood and composition matter most. Teams often pair a model strong on photorealism and adherence for the scene with an editing pass that places the real product.
Packaging, posters and text in images
Ideogram is still the reference for typography; GPT Image 2 handles text-heavy compositions well. Official logos and claims should always be checked and, where needed, rebuilt by hand.
Moodboards and concepts
When the goal is exploring an aesthetic, a model that interprets (like Midjourney) is more useful than one that executes literally.
"A model that follows the prompt perfectly can still get your product wrong. Prompt adherence is a requirement; product fidelity is the outcome."
How to write prompts that get followed
- Subject first, then context. Start with what must be there, then where and how: "amber glass bottle in the center, on white marble, soft side light from the left".
- Bind attributes to the right object. "Matte black cap, cream label" rather than "black, cream, matte": models mix up loosely listed attributes.
- Spell out spatial relations. In front, behind, left, foreground: written, not implied.
- Few, precise numbers. "Three lemons" works; "a dozen different objects" doesn't.
- Format and framing. State aspect ratio, distance, camera angle and lens.
- Reference images whenever a real product exists. No text describes a bottle better than a photo of the bottle.
For brands, product fidelity matters more
Arenas measure whether a model follows a text. A brand needs something else: that the product in the image is that product, with its real shape, color, logo and label. No prompt, however precise, guarantees that on its own.
In our work fidelity comes from three steps: generation guided by real product photos, editing with models that accept reference images, and a human check comparing every image with the original before delivery. The full method is in how to keep product, logo and packaging faithful in AI images; the service is our AI product photography, from €20 per image.
Frequently asked questions
Which text-to-image model follows prompts best?
On Lumenfall's prompt adherence leaderboard updated on 28 July 2026, Google's Nano Banana Pro is first, followed by OpenAI's GPT Image 2 and Black Forest Labs' FLUX.2 [max], with near-identical scores. Rankings change often, so check the live version.
What does prompt adherence mean?
It's a model's ability to generate exactly what the prompt says: objects, quantities, colors, positions, actions and style. It's separate from photorealism and aesthetics, which are scored on their own.
Is the most accurate model also the best for product photos?
Not necessarily. Product photos have to reproduce the real product: that takes reference images, editing and a final human check, on top of a model that follows prompts well.
Which model is best for text inside images?
Ideogram is the reference for text and typography, and GPT Image 2 handles compositions with lettering well. Official logos and claims should always be checked before publishing.
How do I get a model to follow my prompt?
Describe the subject first and then the context, bind each attribute to the right object, spell out positions, use few precise numbers, state format and framing and, if a real product exists, add reference images.