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Average Ratings 0 Ratings

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features
design
support

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Write a Review

Description

DeepSeek-Coder-V2 is an open-source model tailored for excellence in programming and mathematical reasoning tasks. Utilizing a Mixture-of-Experts (MoE) architecture, it boasts a staggering 236 billion total parameters, with 21 billion of those being activated per token, which allows for efficient processing and outstanding performance. Trained on a massive dataset comprising 6 trillion tokens, this model enhances its prowess in generating code and tackling mathematical challenges. With the ability to support over 300 programming languages, DeepSeek-Coder-V2 has consistently outperformed its competitors on various benchmarks. It is offered in several variants, including DeepSeek-Coder-V2-Instruct, which is optimized for instruction-based tasks, and DeepSeek-Coder-V2-Base, which is effective for general text generation. Additionally, the lightweight options, such as DeepSeek-Coder-V2-Lite-Base and DeepSeek-Coder-V2-Lite-Instruct, cater to environments that require less computational power. These variations ensure that developers can select the most suitable model for their specific needs, making DeepSeek-Coder-V2 a versatile tool in the programming landscape.

Description

LongCat-2.0 represents a significant advancement in the realm of language models, featuring a staggering 1.6 trillion parameters through a Mixture-of-Experts architecture that leverages AI ASIC superpods, with approximately 48 billion parameters engaged per token, showcasing exceptional capabilities in coding and agentic tasks. This model marks a notable improvement over its predecessors by integrating a large-scale sparse architecture with specialized post-training methods tailored for tasks in real-world software development, tool utilization, long-context reasoning, and complex agent workflows. Entirely developed and executed on AI ASIC superpods, LongCat-2.0 underwent pretraining that encompassed over 35 trillion tokens and millions of accelerator hours, exemplifying cutting-edge training methodologies on innovative hardware solutions. To enhance its performance on tasks requiring long-term context, the model incorporates LongCat Sparse Attention and is trained using hundreds of billions of tokens from 1M-context datasets, enabling it to effectively manage ultra-long context tasks and ensure robust understanding of lengthy documents. This combination of features positions LongCat-2.0 as a pioneering force in the landscape of advanced language models.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

C Yes 
C# Yes 
C++ Yes 
CSS Yes 
Claude Code No 
Clojure Yes 
Elixir Yes 
F# Yes 
Go Yes 
HTML Yes 
Hermes Agent No 
Java Yes 
Julia Yes 
Kotlin Yes 
OpenClaw No 
Python Yes 
R Yes 
Ruby Yes 
Rust Yes 
TypeScript Yes 

Integrations

C No 
C# No 
C++ No 
CSS No 
Claude Code Yes 
Clojure No 
Elixir No 
F# No 
Go No 
HTML No 
Hermes Agent Yes 
Java No 
Julia No 
Kotlin No 
OpenClaw Yes 
Python No 
R No 
Ruby No 
Rust No 
TypeScript No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
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 No 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
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) Yes 
In Person Yes 

Types of Training

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

Vendor Details

Company Name

DeepSeek

Founded

2023

Country

China

Website

www.deepseek.com

Vendor Details

Company Name

LongCat

Founded

2023

Country

China

Website

longcat.chat/blog/longcat-2.0/

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