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What is Qwen3.5-Plus?

Qwen3.5-Plus is a next-generation multimodal large language model built for scalable, enterprise-grade reasoning and agentic applications. It combines linear attention mechanisms with a sparse mixture-of-experts architecture to maximize inference efficiency while maintaining performance comparable to leading frontier models. The system supports text, image, and video inputs, generating high-quality text outputs suited for analysis, synthesis, and tool-augmented workflows. With a 1 million token context window and support for up to 64K output tokens, Qwen3.5-Plus enables deep, long-form reasoning across extensive documents and datasets. Its optional deep thinking mode allows for expanded chain-of-thought reasoning up to 80K tokens, making it ideal for complex analytical and multi-step problem-solving tasks. Developers can integrate structured outputs, function calling, prefix continuation, batch processing, and explicit caching to optimize both performance and cost efficiency. Built-in tool support through the Responses API includes web search, web extraction, image search, and code interpretation for dynamic multi-agent systems. High throughput limits and OpenAI-compatible API endpoints make deployment straightforward across global applications. With transparent token-based pricing and enterprise-level monitoring, Qwen3.5-Plus provides a powerful foundation for building intelligent assistants, multimodal analyzers, and scalable AI services.

What is PanGu-Σ?

Recent advancements in natural language processing, understanding, and generation have largely stemmed from the evolution of large language models. This study introduces a system that utilizes Ascend 910 AI processors alongside the MindSpore framework to train a language model that surpasses one trillion parameters, achieving a total of 1.085 trillion, designated as PanGu-{\Sigma}. This model builds upon the foundation laid by PanGu-{\alpha} by transforming the traditional dense Transformer architecture into a sparse configuration via a technique called Random Routed Experts (RRE). By leveraging an extensive dataset comprising 329 billion tokens, the model was successfully trained with a method known as Expert Computation and Storage Separation (ECSS), which led to an impressive 6.3-fold increase in training throughput through the application of heterogeneous computing. Experimental results revealed that PanGu-{\Sigma} sets a new standard in zero-shot learning for various downstream tasks in Chinese NLP, highlighting its significant potential for progressing the field. This breakthrough not only represents a considerable enhancement in the capabilities of language models but also underscores the importance of creative training methodologies and structural innovations in shaping future developments. As such, this research paves the way for further exploration into improving language model efficiency and effectiveness.

Media

Media

No images available

Integrations Supported

Alibaba AI Coding Plan
Alibaba Cloud Model Studio
OpenClaw
PanGu Chat
Qwen3.5
Shiori
Tabbit Browser

Integrations Supported

Alibaba AI Coding Plan
Alibaba Cloud Model Studio
OpenClaw
PanGu Chat
Qwen3.5
Shiori
Tabbit Browser

API Availability

Has API

API Availability

Has API

Pricing Information

$0.4 per 1M tokens
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Alibaba

Date Founded

1999

Company Location

China

Company Website

qwen.ai

Company Facts

Organization Name

Huawei

Date Founded

1987

Company Location

China

Company Website

huawei.com

Categories and Features

Categories and Features

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