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features
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support

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Description

CodeQwen serves as the coding counterpart to Qwen, which is a series of large language models created by the Qwen team at Alibaba Cloud. Built on a transformer architecture that functions solely as a decoder, this model has undergone extensive pre-training using a vast dataset of code. It showcases robust code generation abilities and demonstrates impressive results across various benchmarking tests. With the capacity to comprehend and generate long contexts of up to 64,000 tokens, CodeQwen accommodates 92 programming languages and excels in tasks such as text-to-SQL queries and debugging. Engaging with CodeQwen is straightforward—you can initiate a conversation with just a few lines of code utilizing transformers. The foundation of this interaction relies on constructing the tokenizer and model using pre-existing methods, employing the generate function to facilitate dialogue guided by the chat template provided by the tokenizer. In alignment with our established practices, we implement the ChatML template tailored for chat models. This model adeptly completes code snippets based on the prompts it receives, delivering responses without the need for any further formatting adjustments, thereby enhancing the user experience. The seamless integration of these elements underscores the efficiency and versatility of CodeQwen in handling diverse coding tasks.

Description

Qwen3.5-Plus is an advanced multimodal foundation model engineered to deliver efficient large-context reasoning across text, image, and video inputs. Powered by a hybrid architecture that merges linear attention mechanisms with a sparse mixture-of-experts framework, the model achieves state-of-the-art performance while reducing computational overhead. It supports deep thinking mode, enabling extended reasoning chains of up to 80K tokens and total context windows of up to 1 million tokens. Developers can leverage features such as structured output generation, function calling, web search, and integrated code interpretation to build intelligent agent workflows. The model is optimized for high throughput, supporting large token-per-minute limits and robust rate limits for enterprise-scale applications. Qwen3.5-Plus also includes explicit caching options to reduce costs during repeated inference tasks. With tiered pricing based on input and output tokens, organizations can scale usage predictably. OpenAI-compatible API endpoints make integration straightforward across existing AI stacks and developer tools. Designed for demanding applications, Qwen3.5-Plus excels in long-document analysis, multimodal reasoning, and advanced AI agent development.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Alibaba AI Coding Plan No 
Alibaba Cloud Yes 
Alibaba Cloud Model Studio No 
AtCoder Yes 
Code Llama Yes 
Codeforces Yes 
Conda Yes 
DeepSeek Coder Yes 
GPT-4 Yes 
Hugging Face Yes 
LangChain Yes 
LlamaIndex Yes 
ModelScope Yes 
Ollama Yes 
OpenClaw No 
PyTorch Yes 
Python Yes 
Qwen3.5 No 
Shiori No 
StarCoder Yes 

Integrations

Alibaba AI Coding Plan Yes 
Alibaba Cloud No 
Alibaba Cloud Model Studio Yes 
AtCoder No 
Code Llama No 
Codeforces No 
Conda No 
DeepSeek Coder No 
GPT-4 No 
Hugging Face No 
LangChain No 
LlamaIndex No 
ModelScope No 
Ollama No 
OpenClaw Yes 
PyTorch No 
Python No 
Qwen3.5 Yes 
Shiori Yes 
StarCoder No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

$0.4 per 1M tokens
Input: $0.4 per 1M tokens
Output: $2.4 per 1M tokens
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 No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

github.com/QwenLM/CodeQwen1.5

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai

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