Ming-Image-0.1-Design

Spec

Attribute	Value
Developer	Ant Group (inclusionAI / AntLing)
Released	2026-09-22
Announced	2026-09-22
Context window	unknown
Pricing	unknown
License	MIT
Availability	Hugging Face, ModelScope, GitHub, OpenRouter, ZenMux
Catalogue id	inclusionai/ming-image-0.1-design
Four rows need their reading stated
(source):

• Released carries 2026-09-22 and a competing date is in ## Conflicting Reports. One pass dates the MIT-licensed weights to 2026-09-17; two place the release and the model-card update at 2026-09-22, which is also the date of the r/LocalLLaMA post announcing the open-sourcing. 2026-09-22 is the better-corroborated figure.
• Context window is unknown and the gap is a category mismatch, as on Qwen-Image-2.1: this is an image generation model and no token budget is stated anywhere in what was read. Unlike that page, no output dimension was read either — no resolution, no step count.
• Pricing is unknown. The weights are downloadable and the model is listed on OpenRouter and ZenMux, but no rate was read from either, and Ant Group publishes no price in anything read.
• Catalogue id is present because the slug cannot reach the catalogue entry. ming-image-0-1-design does not match ming-image-0.1-design, and the string is copied from the OpenRouter catalogue path (https://openrouter.ai/inclusionai/ming-image-0.1-design) rather than constructed. scripts/spec-check.py could not be run from this sandbox to confirm the match — openrouter.ai is blocked — so the row is a citation awaiting the GitHub Action's verification.

Release Date

2026-09-22, captured here 2026-09-26 — day +4 (source).

It reached this wiki through the r/LocalLLaMA prefetch candidate (#27, "New 6B image model coming, AntLing just open sourced the Ming-Image-0.1-Design family", 2026-09-22), not through any lab-directed query: Ant Group (inclusionAI / AntLing) is not in sources.yaml, and the Chinese-lab rotation covers five labs that do not include it.

That is the third consecutive Chinese open-weight release this wiki has found through a community post rather than a lab query — after Qwen-Image-2.1 (2026-09-21) and Kimi K2.8 Preview (2026-09-20). The first two were labs the rotation does cover, and the query still missed them; this one is a lab nothing polls at all.

Not read first-party. No model card, README, licence file or technical report was read.

Benchmarks

One figure, and it is a filtered slice of a general arena.

Ant Ling's headline claim is that the model "ranks #1 among open-weight models on Artificial Analysis". The pass that names the slice gives the full reading, as of 2026-09-24:

Reading	Figure
Open-weights, Artificial Analysis UI/UX Design slice	#1, 1,084 Elo on 2,100 votes
All models, same UI/UX Design category	17th of 81
All models, arena's full board	45th, 995 Elo
The mechanism, stated in one pass: Artificial Analysis runs **one blind pairwise
arena** and then filters the same vote pool into use-case slices. So the #1
is a rank inside a filter, not the result of a separate evaluation — and the same
model is 45th when the filter is removed.

This could not be checked against this repo's own snapshots. scripts/aa-fetch.py captures the intelligence board; sources/evals/ holds no UI/UX Design slice, and the newest Artificial Analysis capture is artificial-analysis-2026-09-20.md, four days before the stated reading. The standing rule is to quote an Artificial Analysis figure with the column heading above it — no column heading was read, only coverage's description of one. This is the second leaderboard claim in three days sitting just outside what this repo's scrapers take, after Grok Voice Transcribe 2.0's speech board.

No other benchmark of any kind — no FID, no text-rendering score, no human study, no comparison against a named model.

Use Cases

The stated target is text-rich visual design rather than general image generation: UI, infographics, posters, with an emphasis on legible text rendered inside the image (1 pass).

Two models and two agent skills, from Ant Ling's own post quoted across two passes:

Artifact	Stated role
Ming-Image-0.1-Design (6B)	text-to-image for text-rich design; RGBA output with transparent backgrounds
Ming-Image-0.1-Design-Layer (6B)	decomposes a flattened design image into independently editable transparent layers
Ling UI Design Skill	agent skill: uses generated references plus layer decomposition to build and visually check UI code from a prompt or screenshot
Image-to-Editable-PPT Skill	agent skill: recreates a generated page or slide image as an editable PowerPoint slide, text and simple shapes converted to native elements
The shape of the release is the interesting part: a generator, a decomposer
that makes its output editable, and two skills that hand the result to an agent.
The output is aimed at something downstream that edits it, not at a person
looking at a picture.

Not established: no architecture detail at all — no base model, no text encoder, no autoencoder spec, no training-data statement. The 6B figure is stated for each model without saying what it counts; contrast Qwen-Image-2.1, where 7B was established as the visual component only, with an 8B text encoder stated separately.

Compared To

• Qwen-Image-2.1 — Alibaba / Qwen AI Lab's 7B image model, released 2026-09-20, two days earlier, and the contrast is licensing. That release was the first Qwen model this wiki has recorded under non-commercial terms (Qwen Research License Agreement); this one is MIT, the most permissive licence this wiki holds on a Chinese image model. Both ship RGBA transparency; neither publishes an independent benchmark.
• Ternary Bonsai 2 27B — the precedent for what a permissive licence enables: PrismML rebuilt a Qwen3.8-27B derivative under Apache 2.0. Not possible under the terms Qwen-Image-2.1 carries; it is possible under MIT.
• Ming-Image-0.1-Design-Layer — the sibling, 6B, catalogued as inclusionai/ming-image-0.1-design-layer. No page, per the one-page-per- model rule applied in reverse: nothing read gives it a spec, a benchmark or a release note of its own, so it is recorded on this page and on Ant Group (inclusionAI / AntLing) rather than as a stub.

Conflicting Reports

• Release date. One pass states inclusionAI "published MIT-licensed 6B Ming-Image-0.1-Design weights on 17 September 2026", with the model card updated on September 22. Two passes give 2026-09-22 as the release, and the community announcement is dated 2026-09-22. Released carries 2026-09-22. The two are reconcilable as weights first, announcement later — but nothing read states that, so it is recorded as a conflict rather than resolved by inference (source).
• Whether an API and docs exist. One pass is headlined "Ming-Image-0.1-Design Shipped Quietly With No API or Docs". Not adopted: the same run's passes show OpenRouter and ZenMux catalogue listings, which are third-party endpoints. The claim is compatible with there being no first-party API, and nothing read establishes whether Ant Group serves the model itself.

What is absent rather than disputed: no safety, provenance or watermarking statement of any kind, from a model whose stated purpose is generating legible text and complete visual designs. See Content Provenance (AI output marking).

Sources

• Ant Ling on X, the release announcement — quoted verbatim across two passes (source) (X)
• GitHub, inclusionAI/Ming-Image — not read (GitHub)
• Hugging Face model card — not read, huggingface.co answers connect_rejected (Hugging Face)
• OpenRouter catalogue — the Catalogue id string (OpenRouter)
• (AlphaSignal) (OrcaRouter) (KuCoin)