MOSS-Image vs Qwen-Image 2.1 Turbo

Official MOSS-Image teaser collage from the OpenMOSS-Team/MOSS-Image-Base model card — OpenMOSS MOSS-Image-Base card teaser. Source · License: Apache-2.0.

Official Qwen-Image-2.1-Turbo text-to-image preview from the model card assets — Qwen-Image-2.1-Turbo card t2i-preview. Source · License: Qwen Research License.

Verdict. Pick MOSS-Image if you want ungated Apache-2.0 bilingual (en/zh) 5B text-to-image weights with Base and SFT cards. Pick Qwen-Image-2.1-Turbo if you want the accelerated Qwen editing plus T2I checkpoint and accept the Qwen Research License (non-commercial without a separate grant). We have no sourced side-by-side quality test.

Compare MOSS-Image and Qwen-Image-2.1-Turbo.

Dimension	MOSS-Image	Qwen-Image-2.1-Turbo	Source
License	Apache-2.0 (ungated)	other / Qwen Research License (non-commercial without a separate license)	HF LICENSE files (2026-10-19)
Gating	No	No	Hugging Face API
Developer	OpenMOSS	Qwen	Official cards
Parameters	5B (safetensors total 5,082,308,624)	~7.12B (safetensors total 7,115,124,736)	HF API (2026-10-19)
Job	Text-to-image; Base and SFT; JSON layout	Accelerated T2I and image editing (card tags)	Official cards
Languages	en, zh (cardData)	Not independently listed on the turbo card extract	HF cards
Hugging Face likes	291 Base / 339 SFT (2026-10-19)	984 (2026-10-19)	Hugging Face API
Disk (usedStorage)	27,228,815,653 bytes (~25.4 GiB) per card	32,494,210,741 bytes (~30.3 GiB)	Hugging Face API
Weights opened	Cards created 2026-10-11; GitHub public note 2026-10-16	Card created 2026-10-09	HF createdAt
Quality vs Midjourney	Not independently tested	Not independently tested	n/a

When to choose which

Permissive Apache-2.0 weights: MOSS-Image — Apache-2.0 versus Qwen Research License (research/eval unless you get a commercial grant). Not legal advice.
Official image-editing turbo checkpoint: Qwen-Image-2.1-Turbo — Card tags include image-editing. MOSS-Image cards are text-to-image. Unmeasured quality.
Bilingual en/zh prompts and JSON layout: MOSS-Image — Copied from OpenMOSS cards. Not a quality score.
Higher Hugging Face like count this week: Qwen-Image-2.1-Turbo — 984 likes is not a quality ranking.

Read the entity pages: MOSS-Image and Qwen-Image-2.1-Turbo. Both are listed on Midjourney-class alternatives. Related: Iris-3B vs Qwen-Image-2.1-Turbo and FLUX 3 Image Klein vs Qwen-Image-2.1-Turbo.

Key differences

License

MOSS-Image Base and SFT are ungated Apache-2.0 (HF LICENSE + cards, checked 2026-10-19). Qwen-Image-2.1-Turbo is ungated under the Qwen RESEARCH LICENSE AGREEMENT (20 September 2026): research and evaluation only unless you obtain a separate commercial license. Not legal advice.

Job and size

MOSS-Image: bilingual (en/zh) 5B text-to-image, Base plus SFT, JSON layout on the official site. GitHub OpenMOSS/MOSS-Image had 689 stars in the 2026-10-19 check.

Qwen-Image-2.1-Turbo: accelerated Qwen-Image-2.1 checkpoint for text-to-image and editing. HF API safetensors total 7,115,124,736 (~7.12B), 984 likes / 23,131 downloads on 2026-10-19.

Hardware (storage only)

Neither peak-VRAM figure is a forkalt measurement. Disk from HF usedStorage: ~25.4 GiB per MOSS card; ~30.3 GiB for Qwen turbo.

How to choose

Need Apache-2.0 bilingual T2I: MOSS-Image.
Need Qwen editing + turbo T2I and can accept the research license: Qwen-Image-2.1-Turbo.
Need a smaller Apache-2.0 pixel-space checkpoint: Iris-3B.
Need BFL Klein: FLUX 3 Image Klein.

FAQ

Which one looks better?

We have no sourced bake-off. Both publish official preview images. Those are vendor samples, not a forkalt ranking.

Can I use them commercially?

MOSS-Image Base/SFT cards and LICENSE are Apache-2.0 (checked 2026-10-19). Qwen-Image-2.1-Turbo LICENSE is the Qwen RESEARCH LICENSE AGREEMENT (20 September 2026) and grants rights FOR NON-COMMERCIAL PURPOSES ONLY unless you obtain a separate commercial license. Not legal advice.

Can I run both locally?

Both cards are ungated downloads. MOSS-Image usedStorage is ~25.4 GiB per card. Qwen turbo usedStorage is ~30.3 GiB. Peak VRAM is not independently measured.

Why compare these two?

Same search cluster (open Midjourney-class T2I), same week of 2026-10 cards, opposite license stories (Apache-2.0 vs Qwen Research). Iris-3B already has its own vs Qwen page.

Sources & verification

Last verified 2026-10-19 · Last updated 2026-10-19· Edited by forkalt editors · Editorial policy

License notes are not legal advice. Read the original LICENSE. Trademark & disclaimer.