What is DeepSeek-V4-Pro?

DeepSeek-V4-Pro is a next-generation Mixture-of-Experts language model designed to deliver high performance across reasoning, coding, and long-context AI tasks. It features a massive architecture with 1.6 trillion total parameters and 49 billion activated parameters, enabling efficient computation while maintaining strong capabilities. The model supports an industry-leading context window of up to one million tokens, allowing it to process extremely large datasets, documents, and workflows. Its hybrid attention mechanism combines advanced techniques to optimize long-context efficiency and reduce computational requirements. DeepSeek-V4-Pro is trained on over 32 trillion tokens, enhancing its knowledge base and reasoning abilities. It incorporates advanced optimization methods to improve training stability and convergence. The model supports multiple reasoning modes, including fast responses and deep analytical thinking for complex problem solving. It performs strongly across benchmarks in coding, mathematics, and knowledge-based tasks. The architecture is designed for agentic workflows, enabling it to handle multi-step tasks and tool-based interactions. As an open-source model, it offers flexibility for customization and deployment across various environments. It also supports efficient memory usage and reduced inference costs compared to previous versions. The model’s capabilities make it suitable for both research and enterprise applications. Overall, DeepSeek-V4-Pro represents a significant advancement in scalable, high-performance AI with long-context intelligence.

Pricing

Price Starts At:
$0.435 per 1M tokens (input)
Price Overview:
$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 Version available.

Integrations

Offers API?:
Yes, DeepSeek-V4-Pro provides an API

Screenshots and Video

DeepSeek-V4-Pro Screenshot 1

Company Facts

Company Name:
DeepSeek
Date Founded:
2023
Company Location:
China
Company Website:
deepseek.com

Product Details

Deployment
SaaS
Windows
Mac
Linux
On-Prem
Training Options
Documentation Hub

Product Details

Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English

DeepSeek-V4-Pro Categories and Features

DeepSeek-V4-Pro Customer Reviews

Write a Review
  • Reviewer Name: A Verified Reviewer
    Position: Developer
    Has used product for: Less than 6 months
    Uses the product: Daily
    Org Size (# of Employees): 26 - 99
    Cost
    Would you Recommend to Others?
    1 2 3 4 5 6 7 8 9 10

    Great low cost powerful model

    Date: Aug 03 2026
    Summary

    As a heavy user, DeepSeek-V4-Pro feels like a serious workhorse for developers who need long context, strong reasoning, coding ability, and flexibility.

    It is not magic, and it still needs supervision. But for deep coding sessions, agent workflows, large-context analysis, and technical problem-solving, it is one of the most useful models I would keep in my toolkit.

    Positive

    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.

    Negative

    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.

    Read More...
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