whatmodel.sh / image / Muse Image

Muse Image

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

Muse Image is a closed-weights image model from Meta, released July 2026. Licence: proprietary.

76.0±2.1#7 of 144 image modelsfrom 3 benchmark results across 2 sources

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

$ how it compares

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

#modelscorewhereRAMreleased
6Grok Imagine Image 2.0 SpaceXAI79±2api $0.040/image2026-08
7Reve 2.1 Reve78±2api $0.25/image2026-07
8Muse Image Meta76±2api $0.010/image2026-07
9Nano Banana 2 (Gemini 3.1 Flash Image) Google76±1api $0.067/image2026-02
10Nano Banana Pro (Gemini 3 Pro Image) Google76±1api $0.13/image2025-11

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

$ what it's good at

text to image▂▅▅▃▄▄█▃▁▃▁▁ #8 of 126 * · 64% of its score · 1 test

Trails Nano Banana 2 (Gemini 3.1 Flash Image) here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
LMArena text-to-image1274.0 ✎▂▂▃▄▇█▄▂▄▂·▂ beats 68/75avg 1027▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 64%typical
image to image / editing▁▁·▃▂▃█▃▃▄▁▁ #6 of 62 * · 24% of its score · 1 test

Beats Reve 2.1 here, though they rank higher overall.

testresultvs the others in its rundifficultycountswhy
Arena image edit1402.6 ✎▂▁▁▂▆▇█▄▆▅▁▂ beats 47/53avg 1153▇▇▇▇▇▇▇▇▇▇ 24%typical
other tests1 not in a task · 10% of its score
testresultvs the others in its rundifficultycountswhy
Rapidata Benchmark.ai image benchmark (overall Elo)1096.3 ✎▁▁▁▄▂█▂▁▃▂▁▁ beats 27/34avg 875▇▇▇▇ 10%typical

$ where to run it

Through an API

api · $0.010/image · dev.meta.ai ↗ · price sourceUSD per successfully generated image on Meta Model API; flat rate regardless of prompt length, reasoning_strength or built-in web/image search; n images billed as n. Product: Meta Model API image generation. API model: muse-image-1.0. Settings: n=1. Price basis: published list rate. Currency: USD. Meta official pricing page, observed 2026-09-25.

$ how the score was worked out · LMArena leaderboard dataset 88%, Rapidata/text-to-image-human-… 10%

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 dataset2▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 88%CC BY 4.0
Rapidata/text-to-image-human-preference-6M (Benchmark.ai Image Benchmark) published dataset-card rankings1▇▇▇ 10%CC-BY-4.0
prior · pull toward the middle▇ 2%
weighted average= 76.0

$ 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