2026年版：中国のAI画像モデル ベスト7｜実用的なクリエイティブ用途向けランキング

The Best Chinese AI Image Models at a Glance

A “Chinese AI image model” here means an image foundation model developed by a China-based company or research lab. It does not simply mean a model that accepts prompts written in Chinese. That distinction matters: a Western model may understand Chinese, while an Alibaba, ByteDance, Tencent, Baidu, Kuaishou, or Beijing-based startup model may be designed around a different architecture, release strategy, and deployment ecosystem.

How We Ranked the Models

This is not a copy of one leaderboard. A text-to-image score cannot tell you whether a model can preserve a person during an edit, render a bilingual product label, run on available hardware, or be called reliably in production.

The ranking combines five factors:

1. Independent image quality. Blind human-preference results from Artificial Analysis and Arena carry more weight than a vendor’s own launch chart.

2. Editing and reference consistency. A production model must do more than create an attractive first image. It should follow local edit instructions and preserve protected details.

3. Text rendering. We considered both Chinese and English typography, especially for posters, packaging, interfaces, and infographics.

4. Speed, cost, and deployment. Open weights are less useful when the model needs a cluster that most teams cannot afford.

5. Actual access. We distinguish open weights from API-only models and consumer products. “Available in an app” does not mean “deployable in your own stack.”

This produces a ranking for real creative work, not a claim that number one wins every benchmark.

1. Seedream 5.0 Pro: Best Chinese AI Image Model Overall

ByteDance’s Seedream 5.0 Pro takes first place because it performs well across more of the workflow than any other Chinese model on this list. It can generate finished images, edit references, maintain dense layouts, and render multilingual text without forcing users to switch models halfway through a job.

The independent evidence is strong. As of July 2026, Artificial Analysis places Seedream 5.0 Pro eighth overall for text-to-image quality. Arena places it fourth in single-image editing, behind GPT Image 2, Muse Image, and MAI Image 2.5. It is not the global winner in either category. It is, however, the most balanced Chinese model across both.

Where Seedream 5.0 Pro Wins

Seedream is the model I would choose for work that mixes several requirements in one frame:

• a product plus readable packaging;

• a poster with small bilingual text;

• a reference-based character or clothing edit;

• a dense infographic with controlled sections;

• a polished advertising image that must look finished, not merely interesting.

It is also easier to use globally than several China-first products. The Seedream 5.0 Pro API on GPT Proto currently supports 1K and 2K outputs at $0.0405 and $0.081 per image, respectively.

Prompt structure still matters. For new images, describe the complete frame; for editing, name the target change and the details that must remain untouched. The Seedream 5.0 Pro prompt guide explains that distinction with 17 generation and editing examples. If you would rather browse finished ideas before writing from scratch, the Seedream 5.0 Pro prompt collection groups trending prompts and their visual results.

Where It Falls Short

Seedream 5.0 Pro is proprietary. You cannot download the weights, fine-tune the full model locally, or inspect the training pipeline. It also does not lead every independent category. GPT Image 2 still ranks above it for image editing, and specialized typography models can outperform it on certain poster tasks.

The right conclusion is narrower: Seedream is the strongest Chinese all-rounder, not the best model in the world at every image task.

Who Should Use It

Choose Seedream 5.0 Pro if you need one hosted model for marketing assets, e-commerce photography, multilingual posters, high-quality edits, and production-ready keyframes. Skip it if model ownership, offline inference, or custom fine-tuning is a hard requirement.

2. Qwen Image 2.0 Pro: Best for Typography and Structured Design

Qwen Image earned its reputation through text rendering. The original Qwen-Image release introduced a 20B image foundation model focused on complex text and precise editing. The later Qwen Image 2.0 Pro release pushes the family toward native 2K output, denser compositions, multilingual typography, and finished commercial assets.

In Arena’s text-rendering category, the June 2026 build of Qwen Image 2.0 Pro appears close to Seedream 5.0 Pro. Its advantage is less about generic beauty and more about obeying a structured brief: headline, subheading, labels, chart areas, product placement, and visual hierarchy.

Where Qwen Works Well

Qwen Image 2.0 Pro is the stronger choice for:

• bilingual posters with both Chinese and English;

• infographics and presentation graphics;

• menus, packaging, and product cards;

• comic panels with dialogue;

• images where the words are part of the composition rather than an afterthought.

This does not mean every generated paragraph will be perfect. Long-form text inside images still needs proofreading, and a designer should check kerning, punctuation, and small characters before publication.

Qwen Image 2.0 Pro Is Not the Same as Open Qwen-Image

This is the version trap most listicles miss.

The original Qwen-Image and some later checkpoints have downloadable weights. Qwen Image 2.0 Pro should not automatically be described as open source or open weight. It is a later proprietary release distributed through hosted services. A Qwen family name does not guarantee the same license across every version.

That distinction changes the buying decision. If you need Qwen’s newer quality tier, plan around hosted inference. If you need local deployment, evaluate a confirmed open checkpoint such as Qwen Image Max 2512 or the original Qwen-Image instead of assuming the “Pro” label is downloadable.

Where It Falls Short

Qwen Image 2.0 Pro is narrower than Seedream as an overall recommendation. It is excellent when layout and typography dominate the brief, but it does not have the same independent evidence for top-tier editing consistency across broad photographic tasks.

3. HunyuanImage 3.0 Instruct: Best for Complex Scenes and Semantic Editing

Tencent’s HunyuanImage 3.0 Instruct is the most ambitious model in this ranking. It uses a unified autoregressive multimodal architecture rather than a conventional image pipeline, allowing the model to understand an input image, rewrite a sparse prompt, reason about the requested change, and generate the result in one system.

The official model card describes an 80B-parameter mixture-of-experts model with 13B active parameters per token. It supports text-to-image, text-and-image-to-image, prompt rewriting, and chain-of-thought-style planning.

That makes it interesting for difficult prompts:

• place several named subjects in exact spatial relationships;

• edit an object while respecting scene lighting and perspective;

• combine multiple references without losing the role of each;

• turn a short instruction into a more complete visual plan;

• reason through a scene before rendering it.

The Benchmark Result Needs Context

HunyuanImage 3.0 Instruct does not rank near the top of the current open-weight text-to-image leaderboard. Artificial Analysis places it below HiDream O1 Image Dev and ERNIE Image for pure text-to-image preference. Ranking it third here is therefore a judgment about its breadth of semantic editing and multimodal reasoning, not a claim that it produces the prettiest image from every prompt.

If your workload is simple text-to-image generation, ERNIE Image is easier to justify. If the workload contains difficult edits and multi-image instructions, Hunyuan becomes more interesting.

The Hardware Cost Is Severe

The official deployment table recommends at least eight 80GB GPUs for HunyuanImage 3.0 Instruct. That is the opposite of a casual local model. The base text-to-image checkpoint is lighter but still recommends three 80GB GPUs.

Open weights remove one restriction and introduce another: infrastructure. Unless your team already operates a serious GPU cluster, hosted inference or a smaller model will be the rational choice.

4. ERNIE Image: Best Compact Open-Weight Chinese Image Model

Baidu’s ERNIE Image is the sleeper pick of this list. It has an 8B Diffusion Transformer backbone, an Apache 2.0 license, and a clear focus on instruction following and text-heavy visuals. The official model card highlights dense, long-form, and layout-sensitive text for posters, infographics, interfaces, and related designs.

Independent results support the claim. In the July 2026 Artificial Analysis open-weight leaderboard, ERNIE Image ranks fifth overall and second among the Chinese models in this article’s open-weight group, behind HiDream O1 Image Dev 2604.

Why This 8B Model Matters

ERNIE Image is not trying to win through enormous scale. Its appeal is the ratio between quality and operational burden. An 8B model is easier to evaluate, quantize, and integrate than Hunyuan’s 80B MoE system.

It is a good fit for:

• teams building an internal image pipeline;

• Chinese, English, or Japanese text inside graphics;

• self-hosted poster and infographic generation;

• researchers who need inspectable weights;

• developers who want a permissive license.

ERNIE Image vs ERNIE Image Turbo

The standard model prioritizes quality. ERNIE Image Turbo is a distilled 8-step release for faster generation. Choose Turbo when latency or throughput matters more than the last increment of quality; choose the standard model for final assets.

The trade-off is capability range. ERNIE Image is primarily a text-to-image model. It is not the most complete choice for multi-reference editing, subject personalization, or a conversational sequence of revisions.

5. HiDream O1 Image: Best New Unified Open Image Model

HiDream.ai is a Beijing-based lab, and HiDream O1 Image is one of the most technically interesting Chinese AI image models released in 2026. Its Pixel-level Unified Transformer places raw pixels, text, and task conditions in one shared token space. There is no external VAE and no disconnected text encoder.

According to the official model card, the MIT-licensed model supports text-to-image generation, instruction editing, subject-driven personalization, multiple references, layout conditioning, and outputs up to 2048 × 2048.

Why HiDream Is More Than Another Text-to-Image Checkpoint

The model is designed around one continuous workflow. You can generate a subject, edit the image, preserve that subject across new scenes, and use additional references for layout or skeleton control.

Its Dev 2604 checkpoint currently ranks third on Artificial Analysis’s open-weight text-to-image table, above ERNIE Image and HunyuanImage 3.0. That makes HiDream hard to dismiss as a research curiosity.

What the Benchmarks Do Not Prove

The strongest independent text-to-image result belongs to the Dev 2604 checkpoint, while the full unified model sits lower in the same leaderboard. Different variants optimize different jobs. Do not transfer one checkpoint’s score to the whole family.

The ecosystem is also young. Documentation, hosted availability, quantizations, and third-party workflows are still settling. HiDream is the model I would test for a new open visual system, but I would not migrate a production pipeline without running a fixed regression set first.

6. Kling Image 3.0 Omni: Best for 4K Production Assets

Kuaishou is better known internationally for Kling video, but its current image models deserve separate attention. Kuaishou’s February 2026 announcement introduced Image 3.0 and Image 3.0 Omni with 2K and 4K output.

The difference between the two versions is practical:

• Kling Image 3.0 covers generation, local re-editing, style transfer, portrait references, and multi-image blending.

• Kling Image 3.0 Omni adds direct high-resolution output and image-series workflows for consistent characters, products, and environments.

The official Omni guide shows controls for viewpoints, framing, focal length, lighting, expression, multi-reference work, and storyboard-like image series.

Where Kling Fits

Kling Image 3.0 Omni makes the most sense when still images are connected to a larger visual sequence:

• commercial storyboards;

• character turnarounds and multi-view sheets;

• campaign images that reuse the same product;

• consistent frames that may later become video references;

• 4K assets that should not depend on a separate upscaler.

Access Is the Limitation

Kling Image 3.0 Omni is proprietary. Its value is tied to Kling’s product environment and supported commercial access, not to local deployment. Do not confuse it with older open research projects or assume that a Kling video API automatically includes the latest image model.

7. Z-Image Turbo: Best for Speed and Low-Cost Deployment

Z-Image Turbo comes from Alibaba’s Tongyi-MAI group. It is a 6B-parameter distilled model that uses only eight function evaluations. The official model card reports sub-second inference on an H800 and support for 16GB VRAM-class consumer hardware. It is released under Apache 2.0.

That combination makes it unusually accessible. Z-Image Turbo is suitable for:

• bulk thumbnails and social variations;

• rapid prompt iteration;

• internal tools where latency matters;

• local experiments on a single consumer GPU;

• bilingual Chinese and English text generation;

• applications where per-image infrastructure cost matters more than top-tier fidelity.

The Quality Trade-Off Behind Turbo

Distillation is the feature and the limitation. The official comparison describes Turbo as an eight-step generation model with lower diversity and no intended fine-tuning path, while the base Z-Image checkpoint uses more steps and retains more controllability.

Artificial Analysis currently places Z-Image Turbo eighteenth on its open-weight text-to-image leaderboard, below ERNIE Image, HiDream O1 Image, and HunyuanImage 3.0 Instruct. So the honest verdict is simple:

Z-Image Turbo is one of the easiest Chinese image models to deploy, but it is not the best-looking Chinese image model in 2026. Speed is the reason to choose it.

Best Chinese AI Image Model by Use Case

If you only want one recommendation, use Seedream 5.0 Pro. If you need local ownership, start with ERNIE Image for a straightforward text-to-image system or HiDream O1 Image for a broader generation-and-editing workflow.

Open Weights or Hosted API: Which Should You Choose?

Choose open weights when you need offline inference, custom fine-tuning, private infrastructure, or full control over model versions. ERNIE Image, HiDream O1 Image, HunyuanImage 3.0 Instruct, and Z-Image Turbo all offer downloadable checkpoints, but their hardware requirements differ enormously.

Choose a hosted API when you need fast integration, predictable operations, and access to proprietary models such as Seedream 5.0 Pro. The API route avoids GPU procurement and model-serving work, although it also creates vendor dependence and usage-based cost.

The word “open” is not enough. Check four separate items:

1. Are the model weights downloadable?

2. Is the license suitable for commercial use?

3. Can your hardware run the model at the required resolution?

4. Does the open release include the same capabilities as the hosted flagship?

Qwen is the clearest warning. The existence of an open Qwen-Image checkpoint does not make Qwen Image 2.0 Pro open. Version-level verification beats family-level assumptions.

Chinese AI Image Models vs GPT Image and Gemini

Chinese image models are no longer a separate lower tier, but the independent results do not support declaring them the universal winners either.

Seedream 5.0 Pro ranks eighth on Artificial Analysis for text-to-image and fourth on Arena for single-image editing. GPT Image 2 leads Arena’s editing table. That means the best Chinese model is competitive with the global frontier while still trailing on some broad preference tests.

Chinese models have three particularly strong angles:

• Bilingual and non-Latin typography. Seedream, Qwen, ERNIE, and Z-Image explicitly target Chinese and English text.

• Open-weight variety. ERNIE, HiDream, Hunyuan, and Z-Image give developers more self-hosting options than the leading proprietary Western image families.

• Creative workflow specialization. Kling’s image-series tools and Seedream’s dense layout work are aimed at practical content pipelines, not only attractive single images.

GPT Image and Gemini remain safer defaults for teams already committed to their parent ecosystems or for tasks where their editing and multimodal behavior has already been validated. The deciding question is not “China or the West?” It is “Which model fails least often on my fixed prompt and edit set?”

Chinese Image Models That Did Not Make the Top 7

Kolors

Kuaishou’s original Kolors remains an important open image model, but it is no longer the company’s current flagship. More importantly, the frequently repeated name “Kolors 2.1” lacks the same clear first-party release trail as Kling Image 3.0. We would rather rank a verified current model than repeat a questionable version label.

Janus Pro

Janus Pro is useful multimodal research, but its image-generation quality now trails newer dedicated models by a wide margin. Artificial Analysis places it near the bottom of the current open-weight image table. It belongs in a multimodal architecture discussion, not a top 2026 creative-model ranking.

Step Image Edit 2

Step Image Edit 2 is a notable Chinese editing model and may deserve a separate “best image editing models” comparison. It is not a general text-to-image foundation model, so including it in this list would reward a specialist for a different task.

Older Seedream and Qwen-Image Versions

Seedream 4.5, Qwen Image Max 2512, and the original Qwen-Image remain useful. They miss the main list because this ranking favors the strongest current version of a family unless an older open checkpoint offers a clearly different deployment advantage.

How to Access Seedream 5.0 Pro Through GPT Proto

GPT Proto does not currently claim to host every exact model in this top seven. The model available as the direct recommendation from this list is Seedream 5.0 Pro, using the model string dola-seedream-5-0-pro-260628.

The simplest first request uses synchronous mode:

curl --location \
  'https://gptproto.com/api/v3/doubao/dola-seedream-5-0-pro-260628/text-to-image' \
  --header "Authorization: $GPTPROTO_API_KEY" \
  --header 'Content-Type: application/json' \
  --data '{
    "prompt": "Square editorial product photograph of a translucent perfume bottle on wet slate, dramatic side light, realistic glass refraction, fine water droplets, restrained charcoal and silver palette, no text",
    "size": "1024x1024",
    "enable_base64_output": false,
    "enable_sync_mode": true
  }'

The /api/v3/ route uses the raw GPT Proto key in the Authorization header, without a Bearer prefix. For other Chinese image models, check the GPT Proto model gallery for the exact live model string rather than substituting a family name from this article.

Final Verdict

Seedream 5.0 Pro is the best Chinese AI image model in 2026 for most professional users. It wins by being good at several connected tasks—generation, editing, layout, typography, and reference work—while remaining straightforward to access through a hosted API.

Use Qwen Image 2.0 Pro when typography and structured design matter most. Use ERNIE Image when you want a compact, commercially friendly open checkpoint. Use HiDream O1 Image when you want to experiment with one open model across generation, editing, and subject consistency. HunyuanImage 3.0 Instruct is the ambitious semantic editor, but its hardware bill is difficult to defend. Kling Image 3.0 Omni is the high-resolution production specialist. Z-Image Turbo is the throughput choice.

No benchmark can replace your own regression set. Test the same poster, product shot, multi-character scene, identity-preserving edit, and batch-thumbnail prompt on every candidate. The best model is the one that produces the fewest unusable outputs at the quality, speed, and cost your workflow can accept.