PicGens research · Edition 2026-10-04

AI Image Prompt Statistics 2026

Last updated · first published

How do people actually write AI image prompts, and for which models? These statistics come from PicGens’ own corpus of 3,698 published prompts — public creator posts we index together with the image and the full prompt — so they are first-party numbers you can verify, not survey estimates. Each figure belongs to a dated edition with a permanent URL and downloadable data.

Key takeaways

Edition 2026-10-04 · 14 statistics

  1. 1.The PicGens AI image prompt corpus held 3,698 published prompts on October 4, 2026. (PicGens, 2026-10-04)
  2. 2.GPT Image 2 is the AI image model creators share the most prompts for: 56.6% of published prompts (2,094 of 3,698). (PicGens, 2026-10-04)
  3. 3.The Nano Banana family (Nano Banana, Nano Banana 2 and Nano Banana Pro) accounts for 22.8% of published prompts (843). (PicGens, 2026-10-04)
  4. 4.The corpus grew 0.0% since the 2026-09-10 edition, from 3,698 to 3,698 published prompts. (PicGens, 2026-10-04)
  5. 5.Midjourney added 3 prompts since the 2026-09-10 edition, moving its share from 3.1% to 3.2%. (PicGens, 2026-10-04)
  6. 6.Portraits is the most common use case: 56.3% of published prompts carry the Portraits tag (2,081). (PicGens, 2026-10-04)
  7. 7.The median AI image prompt is 1,062 characters (148 words) long; the middle half of prompts run 561–1,793 characters. (PicGens, 2026-10-04)
  8. 8.Nano Banana 2 prompts are the longest (median 1,301 characters) and Nano Banana prompts the shortest (median 433.5) among models with at least 30 prompts. (PicGens, 2026-10-04)
  9. 9.4.4% of prompts (164) are written entirely as structured JSON. (PicGens, 2026-10-04)
  10. 10.24.6% of prompts (910) contain a fill-in [bracket] or {{slot}} placeholder. (PicGens, 2026-10-04)
  11. 11.39.0% of prompts (1,441) ask for visible text in the image, such as a headline, label or slogan. (PicGens, 2026-10-04)
  12. 12.30.0% of prompts name an explicit aspect ratio; 4:5 is the most requested (346 prompts). (PicGens, 2026-10-04)
  13. 13.Brown is the most common dominant colour, tagged on 37.7% of images with colour data. (PicGens, 2026-10-04)
  14. 14.The median source post behind a prompt has 104 likes; Nano Banana Pro posts lead with a median of 302 likes. (PicGens, 2026-10-04)

Every figure is computed from PicGens’ own published prompt corpus and can be reproduced from the CSV or JSON of this edition. Shares use all published prompts as the denominator unless stated otherwise.

Which AI image model do creators share the most prompts for?

GPT Image 2 — 56.6% of the 3,698 published prompts in the 2026-10-04 edition (2,094) were shared for it, followed by Nano Banana Pro at 12.6%. Taken together, the Nano Banana family (Nano Banana, Nano Banana 2 and Nano Banana Pro) accounts for 22.8%. 12.4% of prompts do not name a model and stay in a visible “Unlabelled” bucket rather than being guessed. This is the share of prompts creators chose to publish with a model label, not the market share of each model.

Model share of published prompts, edition 2026-10-04
  • GPT Image 256.6% (2,094)
  • Nano Banana Pro12.6% (465)
  • Unlabelled model12.4% (457)
  • Nano Banana 27.7% (284)
  • Midjourney3.2% (118)
  • Nano Banana2.5% (94)
  • Seedream2.4% (88)
  • Seedance1.6% (58)
  • GPT Image 11.1% (39)
  • Veo0.0% (1)

How many AI image prompts does this dataset cover?

The 2026-10-04 edition covers 3,698 published prompts, the latest ingested on 2026-09-10, with source posts dated up to 2026-08-14. 3,231 of them carry a source-post date; the rest are catalogued reusable templates. Each prompt is stored with its image, the model label the creator gave and keyword-assigned use-case tags.

What do people use AI image prompts for?

Portraits lead: 56.3% of published prompts carry the Portraits tag, ahead of Posters & visuals (42.6%) and Illustration & 3D (34.4%). Tags come from prompt-text keywords and a prompt can carry several, so the shares add up to more than 100%.

Use-case tag share of published prompts, edition 2026-10-04
  • Portraits56.3% (2,081)
  • Posters & visuals42.6% (1,575)
  • Illustration & 3D34.4% (1,273)
  • Ads & product23.5% (868)
  • Prompt templates12.6% (467)
  • Brand & logo10.1% (374)
  • Video7.8% (290)
  • Wallpaper4.7% (175)
  • UI & interfaces1.8% (65)
  • Charts & infographics1.7% (63)

How long is a typical AI image prompt?

The median prompt is 1,062 characters, or 148 words; half of all prompts fall between 561 and 1,793 characters, and the mean is pulled up to 1,364.3 characters by long structured prompts. Length varies by model — the table below lists every model with at least 30 prompts.

Prompt anatomy in the 2026-10-04 edition
Prompt featurePromptsShare of 3,698
Structured JSON prompts1644.4%
Fill-in [slot] or {{slot}} placeholders91024.6%
Ask for visible text in the image1,44139.0%
Name an explicit aspect ratio1,11030.0%
Name a camera setting (mm, f/, ISO, shutter)69418.8%
Written mainly in Chinese, Japanese or Korean2306.2%
Per-model prompt statistics in the 2026-10-04 edition (models with at least 30 prompts)
ModelPromptsMedian charsMedian wordsJSONSlotsIn-image textMedian likes
GPT Image 22,0941,2241694.6%23.2%47.7%95
Nano Banana Pro46597813510.5%29.0%37.4%302
Unlabelled model457645810.7%36.8%24.3%102
Nano Banana 22841,3011952.5%21.1%27.8%107
Midjourney11854873.50.0%19.5%13.6%116
Nano Banana94433.567.54.3%14.9%19.1%85.5
Seedream88971134.50.0%15.9%23.9%89
Seedance58565770.0%3.4%13.8%91.5
GPT Image 1391,18916412.8%23.1%38.5%205

How many prompts are written as JSON or fill-in templates?

4.4% of prompts are written entirely as structured JSON, and 24.6% contain at least one fill-in placeholder such as [subject] or {{product}}. Both are strict pattern definitions (see the method below), so they count only prompts that are unambiguously structured.

How often do prompts ask for text inside the image?

39.0% of prompts ask for visible text in the generated image — a headline, label, slogan, caption or quoted wording — after excluding instructions like “no text”. In-image text is one of the clearest differences between poster, ad and logo prompts and photo prompts.

Which aspect ratios do AI image prompts ask for?

30.0% of prompts name an explicit aspect ratio, and 4:5 is the most requested (346 prompts). Most prompts leave the ratio to the tool’s settings. Among published images with stored dimensions, 73.2% are portrait, 15.0% landscape and 11.8% square.

Aspect ratios named in prompts, share of prompts with text
  • 4:59.4% (346)
  • 9:169.4% (346)
  • 3:45.7% (210)
  • 1:12.7% (99)
  • 16:91.7% (63)
  • 2:31.5% (56)
  • 3:20.5% (17)
  • 4:30.2% (8)
  • 21:90.1% (2)
  • 2:10.1% (2)
  • 1:20.0% (1)
  • 9:210.0% (1)

Which colours dominate AI-generated images in the corpus?

Brown is the most common dominant colour, tagged on 37.7% of the 3,666 images with colour data, followed by Orange (29.1%). Colours are measured from each image’s thumbnail palette (up to three per image), not from the prompt wording.

Dominant colour tags, share of images with colour data
  • Brown37.7% (1,382)
  • Orange29.1% (1,065)
  • Black23.2% (851)
  • White16.2% (595)
  • Blue16.2% (594)
  • Gray16.1% (592)
  • Red9.3% (342)
  • Pink5.8% (211)
  • Yellow5.5% (201)
  • Green4.6% (169)
  • Cyan3.4% (123)
  • Purple1.3% (49)

Which model's prompts get the most engagement?

Nano Banana Pro posts lead with a median of 302 likes among models with at least 30 source posts. Across all 3,231 source posts the median is 104 likes and 45 bookmarks. Posts were collected above a minimum like count, so these medians describe screened, already-popular posts, not typical AI images.

When were these AI image prompts posted?

June 2026 is the busiest source month, with 1,261 prompts — 39.0% of the 3,231 prompts with a source-post date. The month reflects when creators posted, so it mixes real activity with when PicGens collected each source; it is not a demand time series.

How have the statistics changed since the last edition?

The corpus grew 0.0% between the 2026-09-10 and 2026-10-04 editions, from 3,698 to 3,698 published prompts; Midjourney added the most (3 prompts, share 3.1% → 3.2%).

Model counts and shares, 2026-09-10 vs 2026-10-04
Model2026-09-102026-10-04ChangeShare
Midjourney115118+33.1% → 3.2%
GPT Image 22,0932,094+156.6% → 56.6%
Seedance5758+11.5% → 1.6%
Unlabelled model457457012.4% → 12.4%
GPT Image 1393901.1% → 1.1%
Veo1100.0% → 0.0%
Nano Banana Pro466465-112.6% → 12.6%
Nano Banana9594-12.6% → 2.5%
Seedream8988-12.4% → 2.4%
Nano Banana 2286284-27.7% → 7.7%

How should I cite these statistics?

Cite the dated edition, not this page’s latest view: the edition URL and its files never change, so a quoted number stays verifiable after the corpus grows.

Suggested citation

PicGens. (2026, October 4). AI Image Prompt Statistics 2026 (edition 2026-10-04) [Data set]. https://www.picgens.com/research/prompt-trends/2026-10-04

Short attribution

Source: PicGens, AI Image Prompt Statistics 2026, edition 2026-10-04 (https://www.picgens.com/research/prompt-trends/2026-10-04)

How were these statistics calculated?

Every number is an aggregate over the prompts PicGens had published on the edition date: public creator posts that passed collection screening (a minimum like count, a real prompt shared with the image, and quality and takedown review), plus a catalogue of reusable templates. The corpus describes what creators chose to share publicly — it is not a random sample of AI image generation, and model shares are not market shares.

Method

  • Aggregated the 3,698 published rows of the static PicGens catalog snapshot 079d7405 dated 2026-10-04 with scripts/generate-prompt-trends.mjs (metrics prompt-stats-v1).
  • Count rows by stored model label, existing category tag and source-post month; keep “unknown” as a visible bucket instead of inferring a model from prompt wording.
  • Prompt-anatomy metrics (length, JSON, template slots, in-image text, aspect ratios, camera settings, script) are computed from prompt text inside the generator; only counts, medians and definitions are published.
  • Per-model medians and shares are published only for models with at least 30 rows.
  • Do not expose raw prompt contents, row identifiers, creator handles, private fields or per-row behaviour.

Limitations

  • The latest ingested row is 2026-09-10 and the latest source-post date represented is 2026-08-14; this is a dated snapshot, not a live trend feed.
  • The corpus is public creator posts PicGens indexes after screening (minimum likes at collection, a verified prompt, quality and takedown review); it is not a sample of all AI image generation and not model market share.
  • Category tags are keyword-assigned and can overlap, so category totals are not expected to sum to the corpus total.
  • 467 of 3,698 rows carry no source-post timestamp (catalogued templates), so month and engagement figures cover 3,231 rows.
  • Text detectors (JSON, template slots, in-image text, aspect ratios, camera settings) are documented pattern matches, not human review; expect a small error rate in both directions.
  • Engagement counts are stored at the last stats refresh and skew towards posts that passed the collection likes floor.

Metric definitions

published_prompts
Rows of the PicGens catalog that are published (is_published = true) on the edition date, after takedowns and blocked creators are removed.
model_share
Published prompts carrying a stored model label divided by all published prompts. "Unlabelled model" is a visible bucket; no model is inferred from prompt wording.
category_share
Published prompts carrying a category tag divided by all published prompts. Tags are assigned from prompt-text keywords and can overlap, so shares do not sum to 100%.
source_month
Calendar month (UTC) of the source post timestamp. Rows without a source-post timestamp (catalogued templates) are excluded from this dimension.
prompt_rows
Published prompts with non-empty prompt text: the denominator for every prompt-anatomy share.
length_chars
Prompt length in Unicode code points after trimming surrounding whitespace.
length_words
Number of whitespace-separated tokens after trimming. Chinese, Japanese and Korean text has few spaces, so word counts understate those prompts; use characters to compare across languages.
structured_json
The whole prompt (after trimming and removing an optional Markdown code fence) parses as a JSON object or array.
template_slots
The prompt contains at least one fill-in slot: [text] or {{text}} of 1–60 characters with at least one letter, no quotation marks or line breaks, and not followed by "(" (a Markdown link).
in_image_text
The prompt asks for visible text in the image: it uses a text-rendering term (text, lettering, typography, typeface, font, headline, caption, subtitle, slogan, tagline, wordmark, logotype, signage, "the words"; 文字/字样/标题/文案/テキスト/텍스트) or introduces a quoted string with says/reads/title/label/sign/banner — after removing negations such as "no text", "without lettering" or "text-free".
aspect_ratio_mention
The prompt names an explicit aspect ratio W:H from this list: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9, 9:21, 2:1, 1:2 (e.g. "--ar 16:9" or "9:16 framing"), not preceded or followed by another digit, dot or colon.
camera_spec
The prompt names a camera setting: a focal length (e.g. 85mm), an aperture (f/1.8), an ISO value (ISO 200) or a shutter speed (1/250s).
cjk_script
At least 30% of the letters in the prompt are Chinese, Japanese or Korean characters.
image_orientation
From the stored width and height of the first published image: portrait (height > width × 1.05), landscape (width > height × 1.05), otherwise square. Rows without stored dimensions are excluded.
color_tags
Up to three dominant-colour buckets per image, extracted from the thumbnail palette. Share = images carrying the colour divided by images with any colour tag.
engagement
Likes, bookmarks and views of the source post as stored at the last stats refresh, for rows with a source-post timestamp. Views are counted only where a non-zero view count was stored. Medians, not means, because counts are heavily skewed.

Where can I download the data and earlier editions?

Each edition has a permanent page plus CSV and JSON files; the latest files are also always available at /research/prompt-trends.csv and /research/prompt-trends.json. New editions are generated from each new catalog snapshot; earlier editions are never edited.

Read how to write AI image prompts and the other prompt guides, browse prompts by model or use case, or compare Nano Banana 2 vs Pro and Midjourney vs Nano Banana.