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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteIn PicGens’ screened public corpus, prompts are often detailed, portraits are the most common tagged subject, and visible text appears in more than a third of entries. Those findings describe 3,698 published prompt rows in PicGens’ October 4, 2026 edition—not all images made in 2026, all AI users, or the market as a whole.
What this prompt count does—and doesn’t—measure
PicGens’ October 4, 2026 edition contains 3,698 published rows. The site says it indexes public creator posts alongside their images and full prompts, and also catalogs reusable templates. Of the total, 3,231 rows have source-post dates; 467 template rows have no source-post timestamp. The newest source post represented is dated August 14, 2026, and the latest row was ingested on September 10. The October 4 date is the edition date, not a stream of October prompts.
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PicGens describes the collection as a dated snapshot, not a live trend feed. Its public posts passed collection screening that includes a minimum-like threshold, a shared prompt and image, quality review, and takedown review. This favors posts that had already attracted some attention; reusable templates are also included. The corpus is not a random sample of image generation, and its percentages should not be read as population preferences.
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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →The publisher says the figures can be reproduced from the edition’s downloadable CSV or JSON. They summarize stored model labels, existing category tags, source-post month, and pattern-detected prompt features. Unlabelled model records remain unlabelled rather than being inferred from wording. The statistics report does not expose raw prompts, row IDs, creator handles, or private fields. PicGens’ October 4, 2026 edition and methodology provide the definitions and data.
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Which model labels appear most often?
GPT Image 2 is the largest named model-label group in this corpus, with 2,094 rows, or 56.6% of all 3,698. That is a share of PicGens’ published corpus, not market share, model quality, or a measure of how many people use it. The figures describe stored labels; 457 rows (12.4%) are unlabelled.
| Stored model label or family | Rows | Share of 3,698 rows | Median prompt length |
|---|---|---|---|
| GPT Image 2 | 2,094 | 56.6% | 1,224 characters (169 words) |
| Nano Banana Pro | 465 | 12.6% | 978 characters (135 words) |
| Nano Banana family, as defined by PicGens | 843 | 22.8% | Not stated as a family-level median; PicGens reports medians for individual labels |
| Unlabelled | 457 | 12.4% | 645 characters (81 words) |
Rows for Nano Banana Pro are included in the family total; the family figure is not an additional, separate bucket. Other model labels with at least 30 rows show varying median prompt lengths. These are descriptive differences in this collection only; the statistics do not establish that a longer prompt produces a better image.
Median prompt length by model label
| Model label | Median characters | Median whitespace-separated words |
|---|---|---|
| Nano Banana 2 | 1,301 | 195 |
| GPT Image 2 | 1,224 | 169 |
| GPT Image 1 | 1,189 | 164 |
| Nano Banana Pro | 978 | 135 |
| Seedream | 971 | 134.5 |
| Seedance | 565 | 77 |
| Midjourney | 548 | 73.5 |
| Nano Banana | 433.5 | 67.5 |
PicGens reports these per-model prompt medians only for labels with at least 30 rows. The table can show what prompt lengths accompany different labels in this sample; it cannot rank models by output quality, speed, cost, or user satisfaction.
How long are prompts, and what do they ask for?
Across all 3,698 rows, the median prompt is 1,062 characters, or 148 whitespace-separated words. The middle half of prompts falls between 561 and 1,793 characters; the mean is 1,364.3 characters. Character counts are the safer cross-language comparison because whitespace word counts understate text in Chinese, Japanese, and Korean.
- Visible text: 1,441 prompts (39.0%) trigger PicGens’ detector for requests such as headlines, lettering, or typography. It excludes negated directions such as “no text,” but this is pattern matching, not human review.
- Aspect ratio: 1,110 prompts (30.0%) name one. Among prompts that specify a ratio, 4:5 and 9:16 are tied as the most common, with 346 mentions each.
- Reusable slots: 910 prompts (24.6%) contain a fill-in placeholder pattern, such as
[subject]or{{product}}. - JSON: 164 prompts (4.4%) consist entirely of structured JSON under PicGens’ definition: after trimming and optionally removing a Markdown fence, the content parses as a JSON object or array.
These are detected features, not a manual audit of every prompt. PicGens notes that pattern-based measures can produce a small number of false positives and false negatives.
What kinds of images are represented?
Portraits are the most common existing category tag: 2,081 prompts (56.3%) carry it. Posters and visuals appear on 1,575 prompts (42.6%); Illustration and 3D on 1,273 (34.4%); and Ads and product on 868 (23.5%). These keyword-assigned tags overlap, so a prompt can belong to more than one category and the percentages do not add to 100%.
PicGens also reports brown as the most frequent color label: 1,382 of 3,666 images with color data (37.7%). This label comes from thumbnail palettes, not the prompt text, and up to three dominant-color buckets can be assigned to one image. It is therefore a description of the image thumbnails in the catalog, not evidence that creators most often request brown.
Why the month and likes figures need care
June 2026 is the busiest source-post month in the dated portion of the edition, with 1,261 prompts, or 39.0% of the 3,231 rows that have a source-post date. PicGens cautions that this reflects both creator posting dates and when it collected source material; it is not a measure of demand over time. The 467 template rows without source-post dates are excluded from month and engagement calculations.
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The median is 104 likes per dated source post. Nano Banana Pro posts have a reported median of 302 likes among model groups with at least 30 rows. These engagement figures come from posts that passed a minimum-like collection threshold, and likes are refreshed from stored post statistics. They are not typical performance figures for all creators, nor evidence that a particular model label or prompt feature caused engagement.
The October 4 edition changed little from PicGens’ September 10 snapshot: the total remained 3,698, while Midjourney gained three rows. That comparison does not make the corpus a continuous trend series. PicGens’ September 10 public-corpus snapshot likewise distinguishes its catalog counts from search volume, rankings, engagement, and market share.
How to use these findings
The most defensible takeaway is about the contents of one screened public catalog: its prompts are often long, portraits lead its overlapping tags, and requests for visible text, aspect ratios, and reusable placeholders are common enough to count. Model-label shares and prompt-length medians can help describe that catalog, but not decide which model is best or predict what will work for a particular image. Because the collection favors public posts that cleared an engagement threshold, it should not stand in for private experimentation or everyday use.
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