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What is Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next is a pioneering open-weight multimodal Mixture-of-Experts architecture that offers an initial look at the design meant for its successor, Qwen4. This model has been expertly crafted to enhance various aspects such as attention mechanisms, residual pathways, embeddings, and optimization strategies, thereby increasing its overall functionality, enhancing computational efficiency, expanding its model capacity, and ensuring stability during training. Its unique hybrid structure combines Gated DeltaNet, which effectively condenses historical information, with Qwen Sparse Attention, facilitating the selection of meaningful context on a micro-block scale to reduce both attention and indexing expenses for lengthy sequences. The Gated Residual feature enhances the residual pathway by incorporating four streams, which helps in dynamically regulating the information flow across different layers. Moreover, the N-gram Embedding cleverly merges large-scale local-pattern memory with minimal computational overhead for each token, with the capability to transfer to host memory for added efficiency. The entire model is built around a main network comprising 125 billion parameters, supplemented by an additional 51 billion parameters specifically for N-gram embeddings, activating only 6 billion parameters for each token processed. This advanced framework underscores the continuous evolution in machine learning architectures, laying the groundwork for exciting future innovations, and it exemplifies the increasing sophistication and potential of multimodal models in various applications.

What is Gemini 3.5 Flash?

Gemini 3.5 Flash is Google’s next-generation frontier AI model engineered to combine advanced reasoning, multimodal intelligence, agentic automation, and high-speed performance for developers, enterprises, and everyday users. As the first publicly released model in the Gemini 3.5 family, the platform is designed to execute complex long-horizon workflows while delivering fast response speeds and strong performance across coding, reasoning, multimodal understanding, and AI-driven automation tasks. Gemini 3.5 Flash significantly advances Google’s agentic AI capabilities by enabling AI systems to plan, execute, iterate, and manage multi-step workflows such as software engineering, codebase maintenance, financial analysis, application development, infrastructure operations, and large-scale enterprise automation. Powered by the updated Antigravity harness, the model can coordinate collaborative subagents that work together to complete demanding workflows under supervision while maintaining high reliability and operational efficiency. Gemini 3.5 Flash also demonstrates advanced multimodal capabilities by generating dynamic graphics, interactive web interfaces, animations, and visually rich experiences that support developers and businesses building AI-powered applications and user experiences. The model achieves frontier-level performance across multiple coding, agentic, and multimodal benchmarks while operating at significantly faster output speeds compared to many competing frontier AI systems, helping reduce workflow latency and operational costs. Google has integrated Gemini 3.5 Flash across a broad ecosystem that includes the Gemini app, AI Mode in Google Search, Google AI Studio, Android Studio, Gemini Enterprise Agent Platform, and enterprise AI products to provide global access to advanced AI automation capabilities.

Media

Media

Integrations Supported

OfoxAI
OpenClaw
Python
Android Studio
Bind AI
C#
Devin Desktop
Gemini Enterprise
Gemini Enterprise Agent Platform Notebooks
Google AI Studio
Happy Shrimp 1.0
Hugging Face
Lua
Odysseus
Qwen
Qwen Code
R
Ruby
Scala
XML

Integrations Supported

OfoxAI
OpenClaw
Python
Android Studio
Bind AI
C#
Devin Desktop
Gemini Enterprise
Gemini Enterprise Agent Platform Notebooks
Google AI Studio
Happy Shrimp 1.0
Hugging Face
Lua
Odysseus
Qwen
Qwen Code
R
Ruby
Scala
XML

API Availability

Has API

API Availability

Has API

Pricing Information

$2 per 1M (input)
Free Version
Free Trial Offered?

Pricing Information

$1.50 per 1M tokens (input)
Input: $1.50 per 1 million tokens
Output: $9.00 per 1 million tokens
Free Version
Free Trial Offered?

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/blog

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

gemini.google.com

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