Monochrome Song-dynasty landscape inspired by Water Dragon Chant

A literary visual experiment

山河有意
Mountains Remember

Xin Qiji's autumn landscape, imagined through generative image-making.

Color version of the Water Dragon Chant landscape

Grok Imagine Image 2.0

一念成景
A Thought Becomes a Scene

From ink-wash restraint to a vivid, editable world.

ChatGPT rendering of the Water Dragon Chant poem

Words become visible

英雄之淚
A Hero's Tears

A nearly nine-hundred-year-old ci, brought into the present.

Evaluation Report · 8 August 2026

Generative Image Systems and Classical Literature

A comparative visual study using Xin Qiji’s Water Dragon Chant as a shared literary reference.

1. Executive Summary

This report evaluates how three generative image systems represent a classical ci, 《水龍吟·登建康賞心亭》 (Water Dragon Chant · Ascending the Xīn Pavilion in Jiankang). The evaluation considers text rendering, visual composition, atmosphere, and the ability to revise individual elements while preserving the overall scene.

The results are indicative rather than statistically controlled. In this test, ChatGPT produced the most accurate text rendering, while Grok Imagine Image 2.0 showed strong composition, atmosphere, and editability. Gemini produced a less successful result for this particular prompt.

2. Subject and Context

The reference text is associated with 立秋 (Lìqiū), one of the 24 traditional solar terms. The term means “Beginning of Autumn” and marks the seasonal transition into autumn.

The selected author is Xin Qiji (辛棄疾, 1140–1207), an influential literary figure of the Southern Song period. The selected work is a cí (詞) rather than a shī (詩): a classical lyric form shaped by established tonal and rhythmic patterns.

3. Method

The same literary reference was used to assess three systems: Grok Imagine Image 2.0, ChatGPT, and Gemini. The outputs were reviewed qualitatively against four criteria:

Text accuracy: the legibility and correctness of the Traditional characters rendered in the image.

Visual interpretation: the relationship between the generated landscape and the mood of the ci.

Composition: the arrangement of mountains, water, architecture, figures, light, and other visual elements.

Editability: the ability to revise individual components without losing the coherence of the original composition.

4. Findings: Grok Imagine Image 2.0

Approximately 85% of the rendered text appeared correct in the Grok output. This is a strong result for a prompt containing dense Traditional characters and classical literary language.

The system also produced more than a generic mountain background. The scene included distant mountains, autumn water, a pavilion, a scholar, a warrior, a setting sun, and birds. Together, these elements suggested the ci’s combination of ambition, distance, and frustration.

Grok Imagine Image 2.0's rendering of Xin Qiji's 'Water Dragon Chant'
Grok Imagine Image 2.0's rendering of Xin Qiji's Water Dragon Chant (original version)

5. Editability and Iteration

Grok’s most notable strength in this test was the ability to revise individual elements without completely disrupting the composition.

Grok interface showing editable components in the generated image
Grok's component-editing view, showing how individual elements can be adjusted.

The scene was subsequently revised into a color version while retaining its main spatial relationships.

Grok's modified color version of the scene
Grok's modified color version of the scene

6. Motion Output

The revised scene was also converted into a video, extending the experiment from static image generation to animated presentation.

Grok's animated version of Water Dragon Chant

7. Comparative Results

ChatGPT · approximately 95% text accuracy. ChatGPT produced the most accurate Traditional-character rendering in this comparison while also producing a visually coherent result.

ChatGPT's rendering of the poem
ChatGPT's rendering of the poem (95% accuracy)

Grok Imagine Image 2.0 · approximately 85% text accuracy. Its composition, atmosphere, and ability to keep editing the scene were the strongest aspects of its result.

Grok Imagine Image 2.0 scene with yellow flowers
Grok's modified scene with yellow flowers.

Gemini. Its output was less successful than the other two systems in this particular test, especially in the combined treatment of text and visual composition.

Gemini's rendering of the poem
Gemini's rendering of the poem (for reference only)

8. Limitations and Conclusion

This comparison is based on a small qualitative sample rather than a controlled benchmark. The accuracy estimates are observational, and results may change with different prompts, model versions, image settings, or evaluation criteria.

Even with these limitations, the experiment shows how a ci from the Mandarin literary tradition, written nearly 900 years ago, can become something that can be viewed, edited, and set in motion. Generative image systems are therefore useful not only for producing illustrations, but also for exploring how literary mood and imagery can be translated into visual form.

Appendix A · 《水龍吟·登建康賞心亭》
Water Dragon Chant · Ascending the Xīn Pavilion in Jiankang

辛棄疾 · Xin Qiji · Southern Song Dynasty

楚天千里清秋,水隨天去秋無際。 Under the vast Chu sky stretches a thousand miles of clear autumn;
the river flows toward the heavens, and autumn seems without end.
遙岑遠目,獻愁供恨,玉簪螺髻。 I gaze toward the distant hills,
which seem to offer sorrow and regret,
their peaks like jade hairpins and coiled hair.
落日樓頭,斷鴻聲裏,江南遊子。 At sunset upon the tower,
amid the cry of a lone wild goose,
stands a wanderer far from home.
把吳鉤看了,欄杆拍遍,無人會,登臨意。 I look again and again at my sword
and strike the railing in frustration —
yet no one understands
what fills my heart as I stand here.

休說鱸魚堪膾,盡西風,季鷹歸未? Do not speak to me of returning home for fine food.
The west wind is blowing — has Ji Ying returned?
求田問舍,怕應羞見,劉郎才氣。 To seek only fields and houses?
Surely such ambition would be ashamed
before a man of Liu Bei’s spirit.
可惜流年,憂愁風雨,樹猶如此! How sadly the years pass.
I worry over the storms ahead;
even trees grow old — how much more a man?
倩何人喚取,紅巾翠袖,揾英雄淚! Who will call for those in red scarves and green sleeves
to wipe away
a hero’s tears?