whatmodel.sh / image / Kling Image 2.1

Kling Image 2.1

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Kling Image 2.1 is a closed-weights image model from Kuaishou.

52.9±7.0#73 of 144 image modelsfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

Score within the LMArena text-to-image comparison set only.

$ how it compares

The image models ranked either side of Kling Image 2.1, out of 197 with a score.

#modelscorewhereRAMreleased
88LongCat-Image Meituan53±4api $0.13/image +local~15GB2025-12
89Step1X-Edit v1.2 StepFun53±2local~51GB2025-11
90Kling Image 2.1 Kuaishou53±7api $0.014/image
91Imagen 4 Fast Google53±4comparison only2025-08
92Wan 2.5 Image-to-Image Preview Alibaba53±4api $0.030/image2025-09

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$ what it's good at

text to image▂▅▅▃▄▄█▃▁▂▁▁ #63 of 126 * · 79% of its score · 1 test
testresultvs the others in its rundifficultycountswhy
Qwen-Image-Bench (Q-Judger, v1)48.3% ✎█▅▅·▅▅█·█··▃ beats 1/17medium · avg 46%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 79%blunt · at its level

$ where to run it

Through an API

api · Kling AI · $0.014/image · kling.ai ↗ · price sourceUSD per generated image, Kling Image 2.1 text-to-image at 1K or 2K: Kling lists 4 Units ($0.014) per image (1 Unit = $0.0035 list price); image-to-image is 8 Units ($0.028) per image. Product: Kling Image Generation API. API model: Kling Image 2.1. Settings: text-to-image, resolution 1K/2K, one image. Price basis: 4 units × $0.0035 per unit; Kling prints $0.014. Prepaid resource packages. Currency: USD. Kling AI developer pricing page (price table embedded in the page's configuration data), observed 2026-09-25.

$ how the score was worked out · Qwen-Image-Bench: From Genera… 79%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
Qwen-Image-Bench: From Generation to Creation in Text-to-Image Evaluation1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 79%CC-BY-4.0
prior · pull toward the middle▇▇▇▇▇▇ 21%
weighted average= 52.9

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Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated · sources and licences · json