LLM / MoE📅 Released: 2026-04-24

DeepSeek-V4-Pro

1.6T parameter open-source flagship featuring cost-effective 1M context and world-class reasoning.

Overview

DeepSeek-V4-Pro is a 1.6T parameter Mixture-of-Experts (MoE) model released in April 2026. It represents a major milestone for open-source AI, achieving performance that rivals the top closed-source models globally. The model introduces DeepSeek Sparse Attention (DSA) and token-wise compression, enabling it to handle a 1M token context window with unprecedented efficiency. V4-Pro is specifically optimized for agentic capabilities, particularly in coding. It leads all current open models in agentic coding benchmarks and follows only Gemini-3.1-Pro in world knowledge depth. It is designed to be seamlessly integrated with AI agents like Claude Code and OpenClaw.

Unique Factor

The first open-source model to achieve state-of-the-art performance in agentic coding while maintaining a highly cost-effective 1M context window.

Key Capabilities

●

1.6T Total Params

●

Open-Source SOTA Agent

●

1M Context Standard

●

DSA Attention

Benchmarks

MMLU Score

92.5%

HumanEval (Coding)

95%

GPQA Diamond

90%

MATH Benchmark

94%

Top Use Cases

Autonomous Software Engineering

Using agents like Claude Code or OpenCode to autonomously refactor and debug large codebases.

Example: “Scan the entire project for DSA implementation opportunities and refactor the attention mechanism to use DeepSeek Sparse Attention.”

Cost-Effective 1M Context Research

Analyzing entire libraries of research papers at a fraction of the cost of closed-source models.

Example: “Synthesize the findings from these 200 PDFs regarding Ramsey numbers and propose a new asymptotic fact.”

Detailed Features

1.6 Trillion Parameters: Massive model scale with 49B active parameters via MoE.

DeepSeek Sparse Attention (DSA): Novel attention mechanism for ultra-high context efficiency.

1M Context Standard: 1 million token context is the default for all V4 services.

Agentic Coding SOTA: Optimized for autonomous planning and multi-step tool coordination.

Dual-Mode API: Supports both Thinking and Non-Thinking modes for varying task complexity.

Rich World Knowledge: Leading performance across General Knowledge and STEM benchmarks.

✓ Strengths & Pros

• Open-source weights and competitive performance
• World-leading context efficiency and recall
• Highly cost-effective API pricing for 1M tokens
• Strongest open-source agentic capabilities

✕ Limitations & Cons

• Requires significant compute to run locally (1.6T total params)
• Thinking mode latency can be high for complex queries
• Less multimodal support compared to GPT-5.5 (currently focus on LLM/Coding)

Ideal Usage & Target Audience

Best For

Open-source developers, AI agent researchers, and cost-conscious enterprise teams.

Not Recommended For

Users requiring native audio/video modalities (current focus is text/code).

API Implementation

python

import requests

# DeepSeek-V4-Pro API Call
response = requests.post(
    'https://api.deepseek.com/v1/chat/completions',
    json={
        'model': 'deepseek-v4-pro',
        'messages': [{'role': 'user', 'content': 'Explain the DSA attention mechanism.'}],
        'mode': 'thinking'
    }
)

Check the official documentation for full SDK details.