Qwen-Image → the model you reach for when the image has words in it
Qwen-Image renders text other image models garble: twelve scripts natively,
legible down to roughly 10 px, long layout instructions honoured. That is the
reason to pick it, and the prompt should spend its length on the copy and the
layout rather than on adjectives.
Reach it with find_model for text_to_image or image_to_image, then
generate_image / edit_image. Prompts run to 5000 characters; the negative
prompt caps at 500.
Quote the copy
Anything in quotation marks is treated as literal copy. Anything you describe
instead, the model writes for you — usually plausibly and never what you meant.
A vertical science poster. Title "轨道力学" in large bold characters across the
upper third, subtitle "Orbital Mechanics" in small widely-spaced capitals
directly beneath. Three labelled diagram panels down the centre, captions
"近地点", "远地点", "转移轨道" under each. A thin rule separates the diagram block
from a footer reading "第三版 · 2026". Flat editorial illustration, two-colour
palette. No other text.
Three habits that make it land:
- Write the characters, never describe them. Paste the Chinese, Japanese,
Korean or Spanish string itself, with its diacritics. "The Chinese word for
orbit" produces something that is not that word.
- State the relationship between scripts in a bilingual layout — "on the
same line", "stacked directly beneath" — and match their size and weight, or
one language reads as an afterthought.
- Close with "no other text". Left to itself, the model fills empty margins
with invented lettering.
This is the model for copy that is part of the image — a poster, a label, a
sign in the scene. A title or a super on a still headed for a timeline is not:
that goes on as a text clip afterwards (caption-titles), where it can be
corrected and re-timed.
Turn prompt expansion off for typography
On the hosted tiers — Qwen-Image-2, Max and 3 — enable_prompt_expansion
defaults to true and runs an LLM over your prompt first. It helps a three-word
prompt and ruins a typographic one: it edits the strings you quoted and adds
signage you did not ask for. Set it false whenever exact copy matters.
The open-weight checkpoints (fal-ai/qwen-image, the qwen-image-edit-*
releases) have no such flag and take your prompt as written. What they expose
instead is guidance_scale, num_inference_steps and LoRAs — raise guidance
when the layout is being loosely interpreted, and leave the step count alone
until the prompt is settled.
Layout is relative, not metric
Point sizes and pixel coordinates mean nothing here. Vertical order, relative
size and relative weight mean everything. "Large bold capitals across the top,
small widely-spaced capitals directly beneath, body copy in two columns below
the rule" is a layout the model can execute. "24pt heading at x=120" is not.
For dense label sets, add structural marks — rules, borders, panels. Without
them a block of labels renders as a list.