LiblibAI is a leading AI creation platform and community, focusing on AI model sharing for image generation. It offers a vast library of Stable Diffusion models, including Checkpoints and LoRAs, with a special emphasis on anime, gaming, and unique Chinese artistic styles. Users can generate images online or download models for local use.
Shakker is an all-in-one generative AI design platform, offering a vast library of diverse models (including FLUX and Stable Diffusion), integrated professional tools like online ComfyUI and A1111, and powerful features for image generation, editing, and model training. It caters to creators of all skill levels, from beginners to experts.
Product overview
LiblibAI Product overview
LiblibAI is a leading AI creation platform and community, focusing on AI model sharing for image generation. It offers a vast library of Stable Diffusion models, including Checkpoints and LoRAs, with a special emphasis on anime, gaming, and unique Chinese artistic styles. Users can generate images online or download models for local use.
Shakker Product overview
Shakker is an all-in-one generative AI design platform, offering a vast library of diverse models (including FLUX and Stable Diffusion), integrated professional tools like online ComfyUI and A1111, and powerful features for image generation, editing, and model training. It caters to creators of all skill levels, from beginners to experts.
Detailed feature comparison
| Feature | LiblibAI | Shakker |
|---|---|---|
| Primary category | Ai Art | Generative Art |
| Added | 2025-08-01 | 2025-08-15 |
| Pricing | Freemium | Freemium |
| Official website | www.liblib.art | www.shakker.ai |
| Product type | Website | Website |
| Performance data | ||
| User rating | Not verified | Not verified |
| Comments | 0 | 0 |
| Monthly visits | 2.2M | 307.2K |
| Monthly growth | -12.9% | 13.4% |
| Favorites | 106 | 134 |
| Details | View details | View details |
LiblibAI vs Shakker monthly traffic
Compare LiblibAI and Shakker by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the LiblibAI vs Shakker monthly traffic comparison, LiblibAI currently shows 2.2M visits and Shakker shows 307.2K; LiblibAI has about 7.1 times the visible traffic of Shakker, an absolute difference of about 1.9M visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
LiblibAI monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 2.7M Monthly visits
- 2026/1: 2.8M Monthly visits
- 2026/2: 2M Monthly visits
- 2026/3: 2.6M Monthly visits
- 2026/4: 2.5M Monthly visits
- 2026/5: 2.2M Monthly visits
Top regions
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇨🇳China | 93.55% | 2M |
| 🇺🇸United States | 2.95% | 64.1K |
| 🇹🇼Taiwan | 1.53% | 33.3K |
| 🇭🇰Hong Kong | 1.45% | 31.5K |
| 🇸🇬Singapore | 0.52% | 11.3K |
Traffic sources
| Source type | Percentage | Traffic |
|---|---|---|
| Direct | 86.79% | 1.9M |
| Referral | 13.17% | 286.3K |
| 0.04% | 870 |
Search keywords
Shakker monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 671K Monthly visits
- 2026/1: 401.4K Monthly visits
- 2026/2: 310.2K Monthly visits
- 2026/3: 332.8K Monthly visits
- 2026/4: 270.8K Monthly visits
- 2026/5: 307.2K Monthly visits
Top regions
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇨🇳China | 24.8% | 76.2K |
| 🇻🇳Vietnam | 24.56% | 75.4K |
| 🇺🇸United States | 19.93% | 61.2K |
| 🇹🇼Taiwan | 17.24% | 53K |
| 🇧🇷Brazil | 13.47% | 41.4K |
Traffic sources
| Source type | Percentage | Traffic |
|---|---|---|
| Direct | 83.67% | 257K |
| Referral | 16.07% | 49.4K |
| 0.26% | 799 |
Search keywords
Usage comparison
Compare the core capabilities of LiblibAI and Shakker
LiblibAI Core features
Shakker Core features
Use cases
LiblibAI Use cases
Shakker Use cases
LiblibAI vs Shakker:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth LiblibAI vs Shakker comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. LiblibAI is primarily listed under “Ai Art”, while Shakker is primarily listed under “Generative Art”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (LiblibAI: Ai Art; Shakker: Generative Art); Monthly visits (LiblibAI: 2.2M; Shakker: 307.2K); Monthly growth (LiblibAI: -12.9%; Shakker: 13.4%); Favorites (LiblibAI: 106; Shakker: 134); Website (LiblibAI: www.liblib.art; Shakker: www.shakker.ai). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the LiblibAI vs Shakker monthly traffic comparison, LiblibAI currently shows 2.2M visits and Shakker shows 307.2K; LiblibAI has about 7.1 times the visible traffic of Shakker, an absolute difference of about 1.9M visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
If public market visibility is an important first-pass criterion, investigate LiblibAI first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.
Product positioning, use cases, and roles
LiblibAI and Shakker currently overlap in shared categories: Image Generation; shared tags: AI art generator, character design, ComfyUI, lora, and stable diffusion. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
LiblibAI's unique categories/tags are Ai Art, Model Sharing, anime, checkpoint, chinese style, e-commerce design, image generation, and model sharing; Shakker's are Generative Art, Graphic Design, Design Assistant, a1111, concept art, face swap, flux, and image editing. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
LiblibAI has no verified rating, 0 comments, 106 favorites, and 118 likes;Shakker has no verified rating, 0 comments, 134 favorites, and 118 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate LiblibAI first
Put LiblibAI on the priority trial list when the task aligns with “Ai Art” and especially Ai Art, Model Sharing, anime, checkpoint, chinese style, and e-commerce design. This follows recorded positioning and does not imply unlisted capabilities are absent.
LiblibAI also currently records: pricing is freemium, product type is website, 2.2M verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate Shakker first
Put Shakker on the priority trial list when the task aligns with “Generative Art” and especially Generative Art, Graphic Design, Design Assistant, a1111, concept art, and face swap. This follows recorded positioning and does not imply unlisted capabilities are absent.
Shakker also currently records: pricing is freemium, product type is website, 307.2K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in LiblibAI and Shakker, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.
Comparison FAQ
How should I choose between LiblibAI and Shakker?
Where does this comparison data come from?
What do unknown fields mean?
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