# Boogu-Image

> Boogu-Image (Boogu-Image-0.1) is an open-weight image generation and editing family from the Boogu Team, released in June 2026 under Apache 2.0. Every version has 10B parameters: Base, Turbo (4 steps), Edit and Edit-Turbo. It is built for English and Chinese prompts and text rendering. On Kenerate AI it runs in the browser for 18 credits per image or 60 credits per edit with one reference, in 5 aspect ratios.

URL: https://kenerateai.com/models/boogu/boogu-image
Publisher: Kenerate AI (https://kenerateai.com)
Last updated: 31 October 2026

## Key facts
- Official name: Boogu-Image-0.1
- Hugging Face org: Boogu (e.g. Boogu/Boogu-Image-0.1-Base)
- Maker: Boogu Team (boogu-project on GitHub)
- Released: 16 June 2026 (Edit-Turbo 30 June)
- Size: 10B parameters, every variant
- Variants: Base, Turbo, Edit, Edit-Turbo
- Licence: Apache 2.0
- On Kenerate: 18 credits per image · 60 per edit
- Inputs: Text prompt + up to 1 reference image
- Aspect ratios: 5 — 1:1, 3:4, 9:16, 4:3, 16:9

## Steps
1. Open the model — Go to /app/image and pick Boogu Image (the button on this page selects it). Sign in free to get started.
2. Write the prompt — Describe the subject, setting, light and style in English or Chinese. Put any words that must appear in quotes, e.g. a poster that reads "OPEN DAY".
3. Pick a ratio and format — Choose 1:1, 3:4, 9:16, 4:3 or 16:9 and PNG or JPEG, then generate for 18 credits.
4. Edit with one image — To change a photo, upload one image and say what to change and what to keep. An edit costs 60 credits.

## In depth

### Boogu-Image variants at a glance
All four versions share the same 10B size; they differ in task and speed [1]:
- Base — text to image, 25–50 steps, 1K / 1.5K / 2K. The one the team recommends for dense text at 2K.
- Turbo — text to image in 4 steps at 1K, distilled with Decoupled DMD. The ComfyUI default for most prompts [3].
- Edit — one reference image plus an instruction, 25–50 steps, most stable at 1K.
- Edit-Turbo — 4-step editing, released 30 June 2026 and patched on 8 July 2026.

### Text in English and Chinese
Bilingual lettering is what the project is built around: the team says Chinese and English are the focus and that the 3,500 most common modern Chinese characters were repeated in training [1][2]. Put the exact words in quotes, keep them short, and give the layout in plain words ("title at the top, price in the bottom right"). For long paragraphs or tiny type, expect occasional typos — the team says so itself [1].

### Boogu-Image vs Qwen-Image vs Seedream on Kenerate
Pick by input and budget, not by headline score:
- Boogu Image — 18 credits, edit 60 with 1 reference, English + Chinese lettering, 5 ratios.
- Qwen Image — 6 credits, edits 1 uploaded image, strong lettering.
- Qwen Image 3.0 — 9 credits, up to 3 references, 1K or 2K, on the free plan.
- Seedream 5.0 Pro — 13.5 credits at 1K, 27 at 2K, up to 10 references for product and character consistency.

References:
[1] boogu-project/Boogu-Image — GitHub (model zoo, news, hardware table): https://github.com/boogu-project/Boogu-Image
[2] Boogu-Image-0.1 technical report — arXiv 2607.13125: https://arxiv.org/abs/2607.13125
[3] Boogu-Image 0.1 ComfyUI tutorial — Comfy docs: https://docs.comfy.org/tutorials/image/boogu/boogu-image-0.1
[4] Boogu org — Hugging Face: https://huggingface.co/Boogu

## FAQ
Q: What is Boogu-Image?
A: Boogu-Image-0.1 is an open-weight image generation and editing model family from the Boogu Team, published on GitHub as boogu-project/Boogu-Image and on Hugging Face under the Boogu org. It has four 10B-parameter versions — Base, Turbo, Edit and Edit-Turbo — released in June 2026 under Apache 2.0, with a technical report on arXiv (2607.13125).

Q: What is the difference between Boogu Image Base, Turbo, Edit and Edit-Turbo?
A: Base is the full text-to-image model (25–50 steps, 1K to 2K, best for dense text). Turbo is a distilled text-to-image version that needs only 4 steps at 1K. Edit changes an existing picture from one reference image and a text instruction. Edit-Turbo is the 4-step distilled editor, released on 30 June 2026.

Q: How much does Boogu-Image cost on Kenerate?
A: 18 credits per generated image and 60 credits per edit with a reference image — about $0.18–$0.21 and $0.60–$0.69 depending on which credit pack you buy. Packs are one-time purchases with no subscription. Boogu Image is not on the free plan; Qwen Image 3.0 is.

Q: Can Boogu-Image write Chinese and English text in images?
A: Yes — bilingual Chinese and English text rendering is its main focus. The team prioritised the 3,500 most common modern Chinese characters in training. It still warns that long text, small fonts and complex layouts can produce typos or missing characters, and that other languages are not optimised.

Q: Is Boogu-Image made by the Boogu Team an official product?
A: The Boogu Team describes the release as a research project and says it offers no paid API, subscription or commercial service, so paid sites using the name are not affiliated with it. Kenerate AI is not affiliated either: we run a hosted copy of the open Apache 2.0 model so you can use it without a GPU.

Q: How do I use Boogu-Image in ComfyUI?
A: ComfyUI has an official Boogu-Image tutorial with templates for Turbo and Edit. You download the fp8 diffusion model, the Qwen3-VL-8B text encoder and the VAE from Comfy-Org/Boogu-Image on Hugging Face into the matching models folders, then load the workflow. Turbo needs 3–4 sampling steps.

Q: What GPU do I need to run Boogu-Image locally?
A: The GitHub README lists settings from 12 GB up: on 12–16 GB cards you use the fp8 weights with CPU offload, 24–32 GB runs fp8 directly at 1K, and the unquantized Base model is listed for 40–80 GB. In the browser on Kenerate you need no GPU.

Q: Boogu-Image vs Qwen-Image — which should I use?
A: Both handle English and Chinese text. In the Boogu technical report the authors claim state-of-the-art open-source results on Qwen-Image-Bench, but those are author-reported. On Kenerate Qwen Image costs 6 credits and Qwen Image 3.0 costs 9 (free plan, up to 3 references), so start there and try Boogu Image (18 credits) when you want a second open model for bilingual lettering.

Q: Is Boogu-Image good at following prompts?
A: The technical report gives GenEval scores of 0.84–0.85, below HiDream-O1-Image (0.90) and GPT-Image-2 (0.89), and the authors say GenEval differs from human preference. These are the authors' own numbers; we found no independent benchmark yet, so judge it with your own prompts.

## Related pages
- Qwen Image: https://kenerateai.com/model/qwen-image
- Seedream: https://kenerateai.com/model/seedream
- Change text in an image: https://kenerateai.com/change-text-in-image
- Nucleus-Image: https://kenerateai.com/models/nucleusai/nucleus-image
- Open source AI image generator: https://kenerateai.com/open-source-ai-image-generator
- All models: https://kenerateai.com/model

## Sources
- boogu-project/Boogu-Image — GitHub (model zoo, news, hardware table): https://github.com/boogu-project/Boogu-Image
- Boogu-Image-0.1 technical report — arXiv 2607.13125: https://arxiv.org/abs/2607.13125
- Boogu-Image 0.1 ComfyUI tutorial — Comfy docs: https://docs.comfy.org/tutorials/image/boogu/boogu-image-0.1
- Boogu org — Hugging Face: https://huggingface.co/Boogu