DeepSeek-V4: 1M Context, Best Open-Source Agent, Beats Claude Sonnet 4.5

On April 24, 2026, DeepSeek officially released the all-new DeepSeek-V4 series and simultaneously open-sourced it.

Key metrics: 1M (million token) context as standard, achieving best level among open-source models in Agentic Coding evaluation, surpassing all publicly evaluated open-source models in math, STEM, and competitive coding tests.

In practical use, DeepSeek-V4-Pro performs better than Claude Sonnet 4.5, with delivery quality approaching Claude Opus 4.6 non-thinking mode. The model has already become the primary Agentic Coding tool used by DeepSeek’s internal employees.

Starting today, 1M context becomes the standard configuration for all DeepSeek official services.

Two Versions: Pro and Flash, Each with Strengths

DeepSeek-V4 comes in two sizes to meet different scenario needs:

Version	Positioning	Core Advantages	Use Cases
DeepSeek-V4-Pro	Flagship	Strongest Agent capabilities, top-tier reasoning, rich world knowledge	Complex Agent tasks, high-difficulty reasoning, professional Q&A
DeepSeek-V4-Flash	Economy	Reasoning close to Pro, faster speed, lower cost	Simple Agent tasks, daily conversations, batch processing

Both versions come standard with 1M context and support Thinking Mode (Reasoning Mode).

DeepSeek-V4-Pro: Performance Rivals Top Closed-Source Models

1. Significantly Enhanced Agent Capabilities

Here’s the key: DeepSeek-V4-Pro’s Agent capabilities are significantly enhanced.

Agentic Coding Evaluation Performance:

• Achieved the best level among current open-source models
• User experience superior to Claude Sonnet 4.5
• Delivery quality approaching Claude Opus 4.6 non-thinking mode
• Still has some gap with Opus 4.6 thinking mode

The data doesn’t lie: DeepSeek-V4 has become the Agentic Coding model used by DeepSeek’s internal employees.

Excellent Performance Across Agent Evaluations:

• Improved code task performance
• Improved document generation task performance
• Specialized optimization for mainstream Agent products like Claude Code, OpenClaw, OpenCode, CodeBuddy

2. Rich World Knowledge

DeepSeek-V4-Pro in world knowledge evaluation:

• Significantly leads other open-source models
• Only slightly behind top closed-source model Gemini-Pro-3.1

Simply put, its knowledge base is already approaching Google’s top model.

3. World-Class Reasoning Performance

In math, STEM, and competitive coding evaluations, DeepSeek-V4-Pro:

• Surpasses all currently publicly evaluated open-source models
• Achieved performance rivaling world-class closed-source models

Capability Dimension	DeepSeek-V4-Pro	Comparison
Math Reasoning	✅ Surpasses all open-source	Rivals GPT-4o, Claude Opus
STEM Reasoning	✅ Surpasses all open-source	Rivals top closed-source
Competitive Code	✅ Surpasses all open-source	Rivals top closed-source
World Knowledge	✅ Significantly leads open-source	Only slightly behind Gemini-Pro-3.1
Agent Capabilities	✅ Best among open-source	Superior to Sonnet 4.5, approaching Opus 4.6

DeepSeek-V4-Flash: Faster and More Economical Choice

DeepSeek-V4-Flash is positioned as balancing speed and cost:

Performance:

• World knowledge slightly behind Pro
• Reasoning ability close to Pro
• On par with Pro on simple Agent tasks
• Still has gap on high-difficulty Agent tasks

Core Advantages:

• Smaller model parameters and activation
• Provides faster, more economical API service
• Also supports 1M context and thinking mode

Simply put, choose Flash for daily use, Pro for complex tasks.

Black Tech: Novel Attention Mechanism + DSA Sparse Attention

Most eye-catching is DeepSeek-V4’s structural innovation.

Core Technical Breakthrough

DeepSeek-V4 pioneered a novel attention mechanism:

• Compression at token dimension
• Combined with DSA Sparse Attention (DeepSeek Sparse Attention)
• Achieved globally leading long-context capability

Technical Advantages:

• Significantly reduced computational requirements compared to traditional methods
• Significantly reduced memory requirements compared to traditional methods
• Supports 1M context as standard

Performance Comparison

Comparison Dimension	DeepSeek-V4	Traditional Methods
Computation	✅ Significantly reduced	❌ Linear growth with context length
Memory Capacity	✅ Significantly reduced	❌ Linear growth with context length
Context Length	✅ 1M standard	❌ Usually 32K-128K

From now on, 1M (million) context will be standard for all DeepSeek official services.

Specialized Agent Capability Optimization

DeepSeek-V4 has been adapted and optimized for mainstream Agent products:

Agent Product	Optimization
Claude Code	Code tasks, document generation
OpenClaw	Agent framework adaptation
OpenCode	Code generation optimization
CodeBuddy	Programming assistant optimization

Practical Application Scenarios:

• Improved code task performance
• Improved document generation task performance
• Supports generating complex documents like PPTs and reports

How to Use? Three Options

1. Online Chat

Visit chat.deepseek.com or the official App to chat with the latest DeepSeek-V4 and explore the new experience of 1M ultra-long context memory.

2. API Calls

API service has been updated synchronously, supporting:

• OpenAI ChatCompletions interface
• Anthropic interface

Calling Method:

# base_url unchanged, just modify model_name
model_name = "deepseek-v4-pro"  # or "deepseek-v4-flash"

Core Parameters:

• Maximum context length: 1M
• Supports non-thinking mode and thinking mode
• Thinking mode supports reasoning_effort parameter to set thinking intensity (high/max)

Usage Recommendations:

• For complex Agent scenarios, recommend using thinking mode
• Set thinking intensity to max

3. Local Deployment

DeepSeek-V4 is simultaneously open-sourced, supporting local deployment:

Open Source Links:

• Hugging Face: https://huggingface.co/collections/deepseek-ai/deepseek-v4
• ModelScope: https://modelscope.cn/collections/deepseek-ai/DeepSeek-V4

Technical Report:

• https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro/blob/main/DeepSeek_V4.pdf

Important Notice: Old Interfaces Will Be Deprecated

Please note: Two old API interface model names will stop working on July 24, 2026:

• deepseek-chat → will point to deepseek-v4-flash non-thinking mode
• deepseek-reasoner → will point to deepseek-v4-flash thinking mode

Recommend migrating to new model names as soon as possible.

What Can It Do? Countless Scenarios

Application Scenario	Core Capability	Practical Value
Agentic Coding	Code generation, debugging, refactoring	Boost development efficiency, code quality approaching human experts
Document Generation	PPTs, reports, technical docs	Automated content creation, save massive time
Long Text Analysis	1M context understanding	Analyze entire books, complete codebases, long papers
Complex Reasoning	Math, STEM, competitive code	Solve high-difficulty problems, assist research and learning
Knowledge Q&A	Rich world knowledge	Professional domain consulting, knowledge retrieval
Thinking Mode	Deep reasoning	Handle complex logic, provide detailed thinking process

Final Thoughts

The release of DeepSeek-V4 marks the official arrival of the million-context universal era.

It’s no longer about “having long context” to call yourself a long-context model, but achieving: 1M context standard + top-tier reasoning + powerful Agent capabilities + fully open-source.

More importantly, DeepSeek not only released the model but also provided complete API services and open-source weights. Developers can get started immediately, no waiting.

From Agent capabilities perspective, DeepSeek-V4-Pro has reached a level superior to Claude Sonnet 4.5 and approaching Opus 4.6 non-thinking mode. This means open-source models can now compete with top closed-source models in the Agent domain.

From technical innovation perspective, the novel attention mechanism + DSA sparse attention makes 1M context no longer a luxury but standard. The significant reduction in computation and memory requirements means more developers can access ultra-long context capabilities.

The future of AGI may come faster than we think.