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Description

Ornith-1.0 represents an innovative family of models tailored specifically for coding tasks that require agentic capabilities. This family encompasses a wide range of models, from the compact 9B Dense versions ideal for deployment on edge devices to the expansive 397B MoE frontier-scale models designed for peak performance, including variants such as 9B Dense, 31B Dense, 35B MoE, and 397B MoE. Built upon the foundational strengths of pretrained models like Gemma 4 and Qwen 3.5, Ornith-1.0 excels in achieving top-tier performance among open-source models that are similar in size when evaluated against coding benchmarks. A significant breakthrough of this model is its self-improving training framework, which effectively learns to produce both solution rollouts and the tailored scaffolds that direct those rollouts. Rather than depending on static, human-crafted harnesses, Ornith-1.0 perceives the scaffold as a dynamic entity that evolves alongside the policy, enabling the model to optimize both the orchestration of tasks and the resulting solutions in tandem. This dual optimization approach enhances the model's adaptability and effectiveness in real-world coding scenarios.

Description

Qwen3.6-Max-Preview represents an advanced frontier language model aimed at enhancing intelligence, following instructions, and improving real-world agent functionalities within the Qwen ecosystem. This preview builds upon the Qwen3 series, showcasing enhanced world knowledge, refined alignment with instructions, and notable advancements in coding performance for agents, which allows the model to adeptly manage intricate, multi-step tasks and software engineering processes. It is meticulously designed for scenarios requiring advanced reasoning and execution, where the model goes beyond merely generating responses to actively interacting with tools, processing lengthy contexts, and facilitating structured problem-solving in various fields such as coding, research, and enterprise operations. The architecture continues to embody the Qwen commitment to developing large-scale, high-efficiency models that can effectively manage extensive context windows while providing reliable performance across multilingual and knowledge-intensive projects. Moreover, its capabilities promise to significantly enhance productivity and innovation in diverse applications.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Bash Yes 
C# Yes 
Dart Yes 
HTML Yes 
Hugging Face No 
JavaScript Yes 
Kotlin Yes 
Lua Yes 
ModelScope No 
Ollama No 
PHP Yes 
PowerShell Yes 
Qwen No 
Qwen Studio No 
Ruby Yes 
Scala Yes 
Solidity Yes 
Swift Yes 
TypeScript Yes 
Vercel AI Gateway No 

Integrations

Bash No 
C# No 
Dart No 
HTML No 
Hugging Face Yes 
JavaScript No 
Kotlin No 
Lua No 
ModelScope Yes 
Ollama Yes 
PHP No 
PowerShell No 
Qwen Yes 
Qwen Studio Yes 
Ruby No 
Scala No 
Solidity No 
Swift No 
TypeScript No 
Vercel AI Gateway Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Open source
Free Trial Yes 
Free Version Yes 

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 Yes 
iPhone App Yes 
iPad App Yes 
Android App Yes 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
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 No 

Vendor Details

Company Name

DeepReinforce

Country

United States

Website

deep-reinforce.com/ornith_1_0.html

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai/blog

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