whatmodel.sh / image / MetaQuery-XL
MetaQuery-XL
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MetaQuery-XL is an open-weights image model from Meta / NYU, released April 2025.
Model information sources
Score within the LMArena text-to-image comparison set only.
$ how it compares
The image models ranked either side of MetaQuery-XL, out of 197 with a score.
| # | model | score | where |
|---|---|---|---|
| 113 |  Ovis-Image-7B | 48±7 | local |
| 114 |  FLUX.1 Krea [dev] | 47±3 | api $0.025/image +local |
| 115 | MetaQuery-XL | 47±6 | comparison only |
| 116 |  HiDream-I1-Full | 47±2 | api $0.050/image +local |
| 117 |  GLIDE (filtered) | 47±15 | comparison only |
$ what it's good at
text to image▁▂▇▇▆▅█▇▂▃▁▁ #85 of 157 * · 83% of its score · 1 test
Beats Latent Diffusion text2img-large (LDM-KL-8-G, LAION-400M), VQ-Diffusion (ITHQ), Ovis-Image-7B here, though they rank higher overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| WISE (WiScore overall, GPT-4o judge) | 55.0% ✎ | ▄·▆▂▆█▄▆▂▄·▄ beats 16/22 | 83% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · WISE: A World Knowledge-Infor… 83%
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
| source | results | share of the score |
|---|---|---|
 WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation (arXiv v4) | 1 | 83% |
| prior · pull toward the middle | 17% | |
| weighted average | = 46.9 |
$ improve this page
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