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About

DeepSeek-V4-Pro is a large-scale Mixture-of-Experts (MoE) language model designed for advanced reasoning, coding, and long-context understanding. It features 1.6 trillion total parameters with 49 billion activated parameters, enabling high performance while maintaining efficiency. The model supports an exceptionally large context window of up to one million tokens, allowing it to process extensive documents and workflows. It uses a hybrid attention architecture to optimize long-context performance and reduce computational cost. DeepSeek-V4-Pro is trained on over 32 trillion tokens, improving its knowledge and reasoning capabilities. It also includes advanced optimization techniques for stability and faster convergence during training. The model supports multiple reasoning modes, allowing users to balance speed and accuracy based on their needs. Overall, it provides a powerful open-source solution for complex AI tasks and large-scale applications.

About

Foundation models such as GPT-4 have driven rapid improvement in AI. However, the most powerful models are closed commercial models or only partially open. RedPajama is a project to create a set of leading, fully open-source models. Today, we are excited to announce the completion of the first step of this project: the reproduction of the LLaMA training dataset of over 1.2 trillion tokens. The most capable foundation models today are closed behind commercial APIs, which limits research, customization, and their use with sensitive data. Fully open-source models hold the promise of removing these limitations, if the open community can close the quality gap between open and closed models. Recently, there has been much progress along this front. In many ways, AI is having its Linux moment. Stable Diffusion showed that open-source can not only rival the quality of commercial offerings like DALL-E but can also lead to incredible creativity from broad participation by communities.

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

AI researchers, developers, and enterprises seeking a powerful open-source language model for large-scale reasoning, coding, and long-context AI applications

Audience

AI and LLM developers

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

$0.435 per 1M tokens (input)
$0.435 per 1 million input tokens (cache miss), $0.003625 per 1 million input tokens (cache hit), and $0.87 per 1 million output tokens
Free Version
Free Trial

Pricing

Free
Open source
Free Version
Free Trial

Reviews/Ratings

Overall 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

Pros & Cons from Real Users

Pros

  • DeepSeek-V4-Pro is one of those models I keep coming back to because it handles serious work without feeling ridiculously expensive. For coding, repo analysis, long debugging threads, and agent-style workflows, the 1M-token context window is a huge advantage. I also like that it feels strong across both reasoning and implementation. I can use it to think through architecture, explain a messy bug, generate a fix, write tests, and then sanity-check the tradeoffs without constantly switching models. The Pro-Max reasoning mode is especially useful when I need it to slow down and really work through something. It is not the mode I would use for every quick answer, but for hard technical problems, it gives the model a lot more room to reason. The open-weight angle is a big plus too. As someone who uses it heavily, I like having more flexibility than a purely closed API model gives me.

Cons

  • It is still not something I would run on autopilot. For production code, I always review diffs, run tests, and check edge cases because even strong models can make confident mistakes. It can also be overkill for simple tasks. If I just need a quick explanation, small script, or lightweight edit, DeepSeek-V4-Flash may be the better fit. The size is another consideration. Open weights are great, but self-hosting a 1.6T-parameter MoE model is not casual infrastructure.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

DeepSeek
Founded: 2023
China
deepseek.com

Company Information

RedPajama
Founded: 2023
www.together.xyz/blog/redpajama

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Technology Innovation Institute (TII)
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Falcon-7B

Falcon-7B

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Categories

Categories

Integrations

Bash
C
C#
Cheaper Inference
Dart
DeepSeek Harness
Java
JavaScript
Kotlin
Kubernetes
Lua
Novita AI
Objective-C
OfoxAI
PHP
Python
Swift
TypeScript
Vercel AI Gateway
ZooClaw

Integrations

Bash
C
C#
Cheaper Inference
Dart
DeepSeek Harness
Java
JavaScript
Kotlin
Kubernetes
Lua
Novita AI
Objective-C
OfoxAI
PHP
Python
Swift
TypeScript
Vercel AI Gateway
ZooClaw
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