DeepSeek V4 User Manual

DeepSeek V4 User Manual

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AI User Guide

DeepSeek V4 User Manual
Focus: DeepSeek V4-Pro & V4-Pro-Max (2026 Edition)Released: April 24, 2026
Architecture: 1.6 Trillion total parameters (MoE), ~49B active parameters per token
Context Window: Native 1 Million tokens
License: MIT (fully open weights)
Variants: V4-Pro (standard), V4-Pro-Max (maximum reasoning effort), V4-Flash (lighter & cheaper)This manual focuses on V4-Pro and V4-Pro-Max, the high-performance tiers ideal for demanding tasks.

Getting Started

• Platforms: DeepSeek official API, chat.deepseek.com, DeepInfra, Fireworks, Groq (select providers), Hugging Face (self-host).
• Reasoning Modes (especially useful in Pro):
  • Non-Thinking: Fast responses for simple tasks.
  • Think High: Balanced step-by-step reasoning.
  • Think Max (Pro-Max): Highest intelligence — use for complex problems.
• Recommended Settings:
  • Temperature: 0.0–0.3 for coding/math, 0.7–1.0 for creative/general.
  • Top_p: 0.95–1.0.
  • Max tokens: Match your needs (supports very long outputs).

DeepSeek V4-Pro Strenghts

1. Outstanding Coding & Agentic Programming (Strongest Strength)

• Leads or near-leads open-source models and competes closely with frontier closed models.
• SWE-bench Verified: ~80.6% (Pro) — very close to top models.
• LiveCodeBench: 93.5% (often beats Claude Opus 4.7 and others).
• Codeforces Rating: 3206 (top-tier competitive programming).
• Excellent for complex debugging, multi-file refactors, full repository work, and agentic workflows (especially in Pro-Max mode).

2. Extreme Cost Efficiency & Value

• Dramatically cheaper than Claude Opus 4.7 or GPT-5.5 (output tokens often 5–10x less expensive).
• Ideal for high-volume usage, batch processing, and production-scale deployment.
• Best price-to-performance ratio among high-capability models — many users report 10–30x more effective output per dollar when using harnesses/tools.

3. Massive 1 Million Token Context Window

• Native support for 1M tokens with efficient architecture (Compressed Sparse Attention).
• Handles entire large codebases, long documents, books, or massive conversation histories with strong coherence.
• Perfect for long-horizon agentic tasks and deep document synthesis.

4. Powerful Math, STEM & Complex Reasoning (especially in Pro-Max mode)

• Excellent on GPQA Diamond (~90.1%), HMMT, IMO-style problems, and multi-step technical reasoning.
• Pro-Max (maximum reasoning effort) significantly closes the gap with frontier models on hard science, math, and analytical tasks.
• Strong structured thinking and chain-of-thought performance.

5. Open Weights + High Customizability

• Fully open-source (MIT license) with 1.6T total / 49B active parameters (MoE).
• Easy to fine-tune, quantize, self-host, or deploy locally/on-prem.
• Great for building custom agents, domain-specific models, or enterprise solutions.

How to use DeepSeek V4-Pro

Prompt Examples:

Full Repository Analysis

You are an elite senior software architect. Here is the entire codebase [paste or attach files up to 1M tokens].  
Perform a complete architecture review, identify technical debt, security issues, and suggest a modernization roadmap. Output in detailed Markdown with sections.

Bug Fixing with Reproduction

Think step by step in Max mode.  
Here is the failing code and test: [paste].  
Reproduce the bug mentally, then provide a minimal fix with explanation and updated tests.

Agentic Multi-File Refactor

You are an autonomous coding agent. Refactor this project from [old framework] to [new framework].  
Plan first, then execute changes file-by-file. Show diff for each.

Code Generation from Specs

Build a production-ready REST API in Python/FastAPI for [detailed requirements]. Include authentication, rate limiting, logging, Docker, and comprehensive tests.

Code Review & Optimization

Review this pull request [paste code]. Focus on performance, security, readability, and scalability. Rate each file 1-10 and provide improved versions where needed.

Batch Processing

Process the following 50 customer support tickets. For each: summarize issue, classify severity, suggest resolution. Output as CSV.

Data Extraction at Scale

Extract all key financial metrics from these 20 earnings reports. Output structured JSON array.

Content Generation Pipeline

Generate 100 SEO-optimized blog outlines on [topic]. Each outline must include H1, 5 subheadings, and key points.

Automated Testing

Generate unit tests for this function/class [code]. Aim for 95%+ coverage with edge cases.

Daily Report Automation

Analyze this week's sales data [paste]. Create executive summary, charts (describe), and 5 actionable insights.

Entire Book/Document Analysis

You have the full text of [book/document – up to 1M tokens]. Provide a detailed chapter-by-chapter summary, key themes, and critique.

Large Codebase Migration

Here is our entire monorepo [upload files]. Plan and generate migration scripts to move from [legacy] to [new tech stack].

Long Legal/Research Synthesis

Synthesize insights from these 15 research papers [paste all]. Identify contradictions, consensus, and gaps.

Conversation Memory

Review our entire conversation history so far [full context]. Summarize decisions made and create next action plan.

Complex Project Planning

You have the full project specification, requirements doc, and past sprint notes [1M context]. Create a detailed 6-month roadmap with milestones and risks.

Advanced Math Problem

Think Max mode. Solve this competition-level problem step by step with rigorous proof: [math problem].

Physics/Science Simulation

Model and explain the physics behind [phenomenon]. Provide equations, derivations, and numerical example.

Data Science Task

Analyze this dataset [describe or paste]. Perform statistical analysis, find correlations, and suggest ML models.

Algorithm Design

Design an efficient algorithm for [problem] with time/space complexity analysis. Provide Python implementation.

Multi-Step STEM Reasoning

A rocket travels at [params]. Calculate trajectory, fuel requirements, and landing precision. Show all steps.

Fine-Tuning Instruction

Help me create a high-quality fine-tuning dataset for [domain, e.g., legal contract analysis]. Generate 50 diverse examples in the required format.

System Prompt Optimization

You are now [custom persona]. Internalize these rules permanently: [detailed rules]. Respond only according to this persona from now on.

Quantized Model Guidance

I am running 4-bit quantized V4-Pro locally. Suggest prompt adjustments to maintain performance on coding tasks.

Domain Adaptation

Act as a specialized [your industry] expert. Incorporate the following proprietary knowledge: [paste guidelines].

Multi-Agent Setup

Simulate a team of agents (Architect, Coder, Tester, Reviewer) using this model. Coordinate to build [project].

Best Practices Summary

• Use Pro-Max for hardest tasks.
• Structure prompts clearly (Role → Task → Constraints → Format).
• For long context: Provide a “table of contents” or summary first.
• Iterate: Generate → Refine with follow-up prompts.
• Combine with tools (function calling is well-supported).

DeepSeek V4 User Manual
Focus: DeepSeek V4-Pro & V4-Pro-Max (2026 Edition)Released: April 24, 2026
Architecture: 1.6 Trillion total parameters (MoE), ~49B active parameters per token
Context Window: Native 1 Million tokens
License: MIT (fully open weights)
Variants: V4-Pro (standard), V4-Pro-Max (maximum reasoning effort), V4-Flash (lighter & cheaper)This manual focuses on V4-Pro and V4-Pro-Max, the high-performance tiers ideal for demanding tasks.

AI User Guide