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Average Ratings 0 Ratings
Description
Qwen3.8-Flash-Next represents an open-weight multimodal Mixture-of-Experts architecture and serves as an initial glimpse into the design intended for Qwen4. This model strategically enhances attention mechanisms, residual pathways, embeddings, and optimization techniques to boost its capabilities, improve computational efficiency, expand model capacity, and ensure training stability. Its innovative hybrid architecture merges Gated DeltaNet, which adeptly compresses past information, with Qwen Sparse Attention, enabling the selection of significant context at a micro-block level to lessen both attention and indexing costs associated with lengthy sequences. The Gated Residual feature broadens the residual pathway into four streams, dynamically managing the flow of information across different layers. Additionally, the N-gram Embedding integrates large-scale local-pattern memory with minimal added computation per token, and it can be transferred to host memory for further efficiency. The model is structured around a 125B-parameter main network supplemented by 51B parameters dedicated to N-gram embeddings, activating only 6B parameters for each token processed. This sophisticated framework highlights the ongoing advancements in machine learning architectures, setting a promising stage for future developments.
Description
Yi-Lightning, a product of 01.AI and spearheaded by Kai-Fu Lee, marks a significant leap forward in the realm of large language models, emphasizing both performance excellence and cost-effectiveness. With the ability to process a context length of up to 16K tokens, it offers an attractive pricing model of $0.14 per million tokens for both inputs and outputs, making it highly competitive in the market. The model employs an improved Mixture-of-Experts (MoE) framework, featuring detailed expert segmentation and sophisticated routing techniques that enhance its training and inference efficiency. Yi-Lightning has distinguished itself across multiple fields, achieving top distinctions in areas such as Chinese language processing, mathematics, coding tasks, and challenging prompts on chatbot platforms, where it ranked 6th overall and 9th in style control. Its creation involved an extensive combination of pre-training, targeted fine-tuning, and reinforcement learning derived from human feedback, which not only enhances its performance but also prioritizes user safety. Furthermore, the model's design includes significant advancements in optimizing both memory consumption and inference speed, positioning it as a formidable contender in its field.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
01.AI
No
Alibaba Cloud
Yes
Alibaba Cloud Model Studio
Yes
Cherry Studio
Yes
Cline
Yes
Happy Shrimp 1.0
Yes
Hermes Agent
Yes
Hugging Face
Yes
Model Context Protocol (MCP)
Yes
ModelScope
Yes
Integrations
01.AI
Yes
Alibaba Cloud
No
Alibaba Cloud Model Studio
No
Cherry Studio
No
Cline
No
Happy Shrimp 1.0
No
Hermes Agent
No
Hugging Face
No
Model Context Protocol (MCP)
No
ModelScope
No
Pricing Details
$2 per 1M (input)
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
Alibaba
Founded
1999
Country
China
Website
qwen.ai/blog
Vendor Details
Company Name
Yi-Lightning
Country
China
Website
platform.lingyiwanwu.com