Qwen-Image-2.1Alibaba
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Related Products
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About
LMCache is an open source Knowledge Delivery Network (KDN) designed as a caching layer for large language model serving that accelerates inference by reusing KV (key-value) caches across repeated or overlapping computations. It enables fast prompt caching, allowing LLMs to “prefill” recurring text only once and then reuse those stored KV caches, even in non-prefix positions, across multiple serving instances. This approach reduces time to first token, saves GPU cycles, and increases throughput in scenarios such as multi-round question answering or retrieval augmented generation. LMCache supports KV cache offloading (moving cache from GPU to CPU or disk), cache sharing across instances, and disaggregated prefill, which separates the prefill and decoding phases for resource efficiency. It is compatible with inference engines like vLLM and TGI and supports compressed storage, blending techniques to merge caches, and multiple backend storage options.
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About
Qwen-Image-2.1 is a unified text-to-image generation and image editing model in the Qwen family, designed to balance generation quality, inference efficiency, and versatility. Its visual generation component contains 7B parameters and uses 32 Single-Stream DiT layers, with a lightweight architecture that combines mixed-granularity attention and prefix KV cache reuse to deliver strong image quality at lower computational cost. The model natively supports both regular and transparent RGBA image generation, transparent-layer editing, and subject extraction from photographs within a single system. For image editing, it can use up to 10 reference images for multi-subject composition, accept local edit instructions through circles, painted annotations, or separate masks, and preserve the identity of people and products. Improvements to typography, portrait lighting, realistic textures, and fine details are designed to produce more refined and visually compelling results.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
AI engineers and infrastructure teams looking for a tool to lower latency, reduce compute cost, and scale throughput
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Audience
Developers, researchers, and creative AI teams seeking to generate, edit, compose, and manipulate high-quality images with an open source multimodal generation model
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationLMCache
United States
lmcache.ai/
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Company InformationAlibaba
Founded: 1999
China
github.com/QwenLM/Qwen-Image-2.1
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Categories |
Categories |
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Integrations
Happy Shrimp 1.0
Not Supported
Qwen
Not Supported
Qwen Studio
Not Supported
QwenCloud
Not Supported
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Integrations
Happy Shrimp 1.0
Supported
Qwen
Supported
Qwen Studio
Supported
QwenCloud
Supported
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