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Ideogram 4.5

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Ideogram 4.5 is a closed-weights image model from Ideogram. Licence: proprietary.

Catalogue identity notes

Exact Arena entry 'ideogram-4.5' in the October 2026 pinned dataset. Comparison identity; no public run route inferred from leaderboard inclusion.

67.6±3.4comparison only: no current run option verifiedfrom 2 benchmark results across 2 sources* 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 Ideogram 4.5, out of 197 with a score, then more from Ideogram.

#modelscorewhereRAMreleased
17GPT Image 1.5 OpenAI71±1api $0.034/image2025-12
18Qwen-Image-2.1 Alibaba69±2local~12GB2026-09
19Ideogram 4.5 Ideogram68±3comparison only
20Qwen-Image-2.0-Pro (2026-06-22) Alibaba67±2api $0.075/image2026-06
21Uni-1.1 Luma AI67±2api $0.040/image2026-05
more from Ideogram
23Ideogram 4.0 Ideogram66±2api $0.060/image +local~6.1GB2026-06
94Ideogram 3.0 Ideogram52±2api $0.060/image2025-03
118Ideogram 2.0 Ideogram46±2api $0.080/image

see all image models · find the ones that fit your machine

$ what it's good at

image to image / editing▁▁▁▃▂▃█▃▃▃▁▁ #17 of 81 * · 67% of its score · 1 test

Beats Nano Banana 2 Lite (Gemini 3.1 Flash-Lite Image), GPT Image 1.5 here, though they rank higher overall. Trails Grok Imagine Image Pro here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Arena image edit1347.4 ✎▂▁▁▂▆▇█▄▆▅▁▂ beats 37/53avg 1153▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 67%typical
other tests1 not in a task · 28% of its score
testresultvs the others in its rundifficultycountswhy
Rapidata Benchmark.ai image benchmark (overall Elo)967.6 ✎▁▁▁▄▃█▂▁▁▂▁▁ beats 11/34avg 875▇▇▇▇▇▇▇▇▇▇▇ 28%typical

$ where to run it

No verified API or download recorded yet · add one

$ how the score was worked out · LMArena leaderboard dataset 67%, Rapidata/text-to-image-human-… 28%

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
LMArena leaderboard dataset1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 67%CC BY 4.0
Rapidata/text-to-image-human-preference-6M (Benchmark.ai Image Benchmark) published dataset-card rankings1▇▇▇▇▇▇▇▇ 28%CC-BY-4.0
prior · pull toward the middle▇▇ 5%
weighted average= 67.6

$ improve this page

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