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ERNIE-Image-Turbo
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ERNIE-Image-Turbo is an open-weights image model from Baidu, released April 2026. Its published size is 8B parameters. Licence: apache-2.0.
Score within the LMArena text-to-image comparison set only.
$ how it compares
The image models ranked either side of ERNIE-Image-Turbo, out of 197 with a score.
| # | model | score | where |
|---|---|---|---|
| 45 | 61±1 | api $0.040/image | |
| 46 | 61±3 | api $0.21/image | |
| 47 | 61±3 | api $0.010/image +local | |
| 48 | 60±5 | local | |
| 49 | 60±2 | api $0.030/image +local |
$ what it's good at
text to image▂▅▅▃▄▄█▃▁▂▁▁ #32 of 126 · 96% of its score · 5 tests
Beats Wan 2.7 Image Pro, Wan 2.7 Image, Imagen 4 Ultra here, though they rank higher overall. Trails ERNIE-Image here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LongText-Bench (EN) lab | 96.0% ✎ | ▃·····▅██▅▃▃ beats 10/12 | 25% |
| LongText-Bench (CN) lab | 96.8% ✎ | ▃·······████ beats 10/12 | 20% |
| GenEval lab | 86.7% ✎ | ▇▃▅▇▁▄▅▃█▃▃▅ beats 34/39 | 19% |
| OneIG-Bench (CN) lab | 50.6% ✎ | ▃·▃█▃·▃··▃·▃ beats 2/8 | 16% |
| OneIG-Bench (EN) lab | 53.4% ✎ | ▃······▃▅█▅▃ beats 4/9 | 16% |
$ where to run it
Through an API
api · fal.ai · $0.010/image · fal.ai ↗ · price sourceUSD for one 1-megapixel output: fal bills this endpoint $0.01 per output megapixel (price = rate × 1 MP; fal's rounding for 1024×1024 ≈ 1.05 MP is not stated; larger outputs cost proportionally more). Product: fal.ai serverless text-to-image (Turbo, 8 steps default). API model: fal-ai/ernie-image/turbo. Settings: 1 MP output, num_images=1. Price basis: published per-megapixel list rate × 1 MP. Currency: USD. Not a Baidu direct tariff. fal.ai official model page, observed 2026-09-25.
Other ways to run it
version
- Run it as published · needs ~17.1 GB · from github.com/leejet
sd-cli --diffusion-model models/ernie-image-turbo-UD-Q4_K_M.gguf --vae models/flux2_ae.safetensors --llm models/ministral-3-3b.safetensors -p "a lovely cat" --cfg-scale 1.0 --steps 8 -v --offload-to-cpu --diffusion-fa
Official weights and documentation: huggingface.co/baidu ↗
$ how the score was worked out · ERNIE-Image model repository… 96%
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 |
|---|---|---|
| 5 | 96% | |
| prior · pull toward the middle | 4% | |
| weighted average | = 60.5 |
$ 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