CodeQwen

CodeQwen

Alibaba
Java

Java

Oracle
Qwen2.5-1M

Qwen2.5-1M

Alibaba
+

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About

CodeQwen is the code version of Qwen, the large language model series developed by the Qwen team, Alibaba Cloud. It is a transformer-based decoder-only language model pre-trained on a large amount of data of codes. Strong code generation capabilities and competitive performance across a series of benchmarks. Supporting long context understanding and generation with the context length of 64K tokens. CodeQwen supports 92 coding languages and provides excellent performance in text-to-SQL, bug fixes, etc. You can just write several lines of code with transformers to chat with CodeQwen. Essentially, we build the tokenizer and the model from pre-trained methods, and we use the generate method to perform chatting with the help of the chat template provided by the tokenizer. We apply the ChatML template for chat models following our previous practice. The model completes the code snippets according to the given prompts, without any additional formatting.

About

The Java™ Programming Language is a general-purpose, concurrent, strongly typed, class-based object-oriented language. It is normally compiled to the bytecode instruction set and binary format defined in the Java Virtual Machine Specification. In the Java programming language, all source code is first written in plain text files ending with the .java extension. Those source files are then compiled into .class files by the javac compiler. A .class file does not contain code that is native to your processor; it instead contains bytecodes — the machine language of the Java Virtual Machine1 (Java VM). The java launcher tool then runs your application with an instance of the Java Virtual Machine.

About

Qwen2.5-1M is an open-source language model developed by the Qwen team, designed to handle context lengths of up to one million tokens. This release includes two model variants, Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M, marking the first time Qwen models have been upgraded to support such extensive context lengths. To facilitate efficient deployment, the team has also open-sourced an inference framework based on vLLM, integrated with sparse attention methods, enabling processing of 1M-token inputs with a 3x to 7x speed improvement. Comprehensive technical details, including design insights and ablation experiments, are available in the accompanying technical report.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Anyone seeking an AI tool to improve their natural language understanding operations and text generation tasks

Audience

Developers looking for a Programming Language solution

Audience

AI researchers, developers, and organizations seeking an open-source large language model with extended context capabilities for advanced natural language processing tasks

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Alibaba
Founded: 1999
China
github.com/QwenLM/CodeQwen1.5

Company Information

Oracle
docs.oracle.com/javase/8/docs/technotes/guides/language/index.html

Company Information

Alibaba
Founded: 1999
China
qwenlm.github.io/blog/qwen2.5-1m/

Alternatives

CodeGemma

CodeGemma

Google

Alternatives

Alternatives

Qwen2.5-Max

Qwen2.5-Max

Alibaba
Qwen-7B

Qwen-7B

Alibaba
Qwen2

Qwen2

Alibaba
CodeQwen

CodeQwen

Alibaba
Qwen2.5-Max

Qwen2.5-Max

Alibaba
Qwen3-Max

Qwen3-Max

Alibaba
Qwen3-Max

Qwen3-Max

Alibaba
Qwen2

Qwen2

Alibaba

Categories

Categories

Categories

Integrations

Actian Ingres
Arachnophilia
BaseRock AI
Benerator
CI Fuzz
Caduceus
EditRocket
Gemini 3 Deep Think
Gerrit Code Review
Klavis AI
Mockito
ORMIT™-APEX
PDFmyURL
Percept Insight
Qwen-7B
RallyHere
SendSafely
Service Objects Email Validation
Speakeasy
Syntho

Integrations

Actian Ingres
Arachnophilia
BaseRock AI
Benerator
CI Fuzz
Caduceus
EditRocket
Gemini 3 Deep Think
Gerrit Code Review
Klavis AI
Mockito
ORMIT™-APEX
PDFmyURL
Percept Insight
Qwen-7B
RallyHere
SendSafely
Service Objects Email Validation
Speakeasy
Syntho

Integrations

Actian Ingres
Arachnophilia
BaseRock AI
Benerator
CI Fuzz
Caduceus
EditRocket
Gemini 3 Deep Think
Gerrit Code Review
Klavis AI
Mockito
ORMIT™-APEX
PDFmyURL
Percept Insight
Qwen-7B
RallyHere
SendSafely
Service Objects Email Validation
Speakeasy
Syntho
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