How to Use DeepSeek: Complete Guide (2026)

Last verified: May 7, 2026  ·  Format: Guide  ·  Est. time: 15-20 min

DeepSeek is one of the most capable open-weight large language models available in 2026, and it is entirely free to start using. Whether you want to chat through a browser, integrate the API into a development workflow, or self-host the model on your own infrastructure, DeepSeek provides a path for each scenario. This guide walks through every step, from account creation to selecting reasoning modes to running the model locally.

As of May 2026, DeepSeek's flagship V4 series offers a 1-million-token context window, competitive benchmark performance, and API pricing that undercuts every major Western provider. V4-Flash processes input at $0.14 per million tokens. V4-Pro costs $1.74 per million tokens, according to DeepSeek's published pricing (April 2026). One critical consideration: DeepSeek is built and operated by a Chinese AI lab, and its data handling practices carry real privacy implications that you should evaluate before sending sensitive information through the hosted platform.

What You Need Before Starting

DeepSeek is built by DeepSeek, a Chinese AI research lab founded in 2023 as a subsidiary of the quantitative trading firm High-Flyer. The consumer chat interface lives at chat.deepseek.com. A separate API exists for developers at platform.deepseek.com.

Step 1: Access the Free Web App

The fastest way to start using DeepSeek requires no account, no installation, and no payment.

1. Navigate to chat.deepseek.com in your browser. The interface loads immediately.
2. Toggle between two modes at the top of the chat window:
   • Instant Mode (V4-Flash): Fast, cost-efficient responses. Activates 13B of 284B total parameters.
   • Expert Mode (V4-Pro): Deeper reasoning. Activates 49B of 1.6T total parameters.
3. Start chatting. The 1-million-token context window is active by default. You can paste lengthy documents, upload files, and enable web search directly.
4. Create an account to save conversation history and unlock API credits (5 million free tokens).

DeepSeek is also available as a free mobile app for iOS and Android, offering the same model access as the web interface.

How to Access DeepSeek

Step 2: Set Up API Access

For developers building applications, automations, or agentic workflows, the API provides programmatic access to all DeepSeek models.

1. Create a developer account. Go to platform.deepseek.com and register. No credit card required. You receive 5 million free tokens (valid for 30 days).
2. Generate an API key. Navigate to the API Keys section and create a new key. Copy and store it securely.
3. Make your first API call. DeepSeek's API is OpenAI-compatible. Change the base_url and swap your API key:

import openai

client = openai.OpenAI(
    api_key="YOUR_DEEPSEEK_API_KEY",
    base_url="https://api.deepseek.com/v1"
)

response = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain mixture-of-experts in two paragraphs."}
    ],
    max_tokens=4096,
    temperature=0.6
)

print(response.choices[0].message.content)

Migration note: The legacy model names deepseek-chat and deepseek-reasoner point to V4-Flash during the transition but will be retired on July 24, 2026. Update your model parameters before that date.

DeepSeek also provides an Anthropic-compatible endpoint at https://api.deepseek.com/anthropic for teams using Anthropic's SDK format. Most frameworks (LangChain, LlamaIndex, Vercel AI SDK) support DeepSeek out of the box by swapping the base URL.

Step 3: Choose the Right Reasoning Mode

DeepSeek V4 models support three reasoning effort levels. Selecting the right mode directly impacts response quality, latency, and cost.

Non-Think bypasses chain-of-thought entirely. No block is generated. Use this for routine daily tasks and high-volume API pipelines.

Think High generates a visible block with step-by-step logical analysis before delivering the final answer. This is the default for complex problem-solving.

Think Max injects a system prompt instructing the model to apply maximum effort, stress-test logic against edge cases, and document all rejected hypotheses. Requires at least 384K tokens of context. Reserve this for boundary-testing scenarios.

Step 4: Use Key Features

Coding and Software Engineering

DeepSeek V4-Pro self-reports an 80.6% resolution rate on SWE-bench Verified and a Codeforces Elo rating of 3,206, according to DeepSeek's technical report (April 2026). The model integrates with developer tools including Claude Code, OpenCode, and OpenClaw for agentic coding workflows.

Mathematics and Formal Reasoning

DeepSeek-R1 achieved 97.3% on MATH-500, as reported by DeepSeek. The newer V4-Pro-Max scores 95.2% on HMMT 2026 Feb competition problems, according to DeepSeek's evaluation results. For formal theorem proving, the specialized DeepSeek-Prover-V2-671B model generates verified Lean 4 proofs.

Search and Agentic Workflows

V4 preserves complete reasoning history across all tool-result rounds and user messages. An agent can chain 100+ tool calls while maintaining a coherent chain of thought, solving the context-loss problem that affected earlier versions during multi-step tasks.

1-Million-Token Context Window

Both V4-Pro and V4-Flash support a 1-million-token context window by default. The hybrid attention architecture reduces compute to 27% of FLOPs and 10% of KV cache compared to V3.2, according to DeepSeek's technical report. Practical applications include analyzing entire code repositories in a single pass and maintaining coherent agent memory across extended workflows.

Step 5: Run DeepSeek Locally (Self-Hosting)

Self-hosting is the recommended path for organizations that cannot send data to servers in China. All DeepSeek models are released under the MIT License, allowing commercial use, modification, and redistribution with no restrictions.

Hardware Requirements

Source: DeepSeek technical documentation and Hugging Face model cards (April 2026).

Quick Start with Ollama (Distilled Models)

For practitioners who want to test DeepSeek reasoning locally without enterprise hardware:

# Install Ollama (macOS/Linux)
curl -fsSL https://ollama.com/install.sh | sh

# Pull and run DeepSeek R1 distilled 7B model
ollama run deepseek-r1:7b

This runs on consumer hardware and keeps all data entirely local. For production deployments, use vLLM (supports FP8/BF16, pipeline parallelism) or SGLang (state-of-the-art latency on NVIDIA and AMD GPUs).

Step 6: Reduce Costs with Caching and Batching

DeepSeek's API pricing is already significantly lower than competitors, but three strategies reduce costs further:

1. Maximize prefix cache hits. Structure prompts so system instructions and static context appear first. Cache hits reduce input cost from $0.14/M tokens to approximately $0.03/M tokens, a 90% reduction.

2. Schedule batch processing during off-peak hours. DeepSeek offers up to 75% off R1 models and 50% off V4 models during 16:30-00:30 UTC. For workloads that tolerate scheduling flexibility, this is the largest cost lever.

3. Choose the right model for the task. Use V4-Flash (Non-Think) for high-volume, low-complexity tasks. Reserve V4-Pro (Think High or Think Max) for problems requiring deep reasoning. Flash costs 12x less than Pro per token.

Step 7: Understand Limitations and Data Privacy

China Data Residency

DeepSeek's privacy policy states all personal information is stored on servers in the PRC. The U.S. House Select Committee on the CCP concluded in March 2025 that the app functions as a direct channel to funnel user data into Chinese state infrastructure via backend connections to China Mobile, a state-owned telecom designated as a Chinese military company. Italy's Garante blocked DeepSeek in January 2025 after the company claimed GDPR does not apply to it. Multiple EU regulators in France, Ireland, Germany, Belgium, and Portugal launched subsequent investigations.

Practical guidance: If your organization operates under GDPR, CCPA, HIPAA, or handles classified information, do not use DeepSeek's hosted API for production workloads containing sensitive data. Use the open-weight models via self-hosting instead, where no data leaves your infrastructure.

Content Censorship

Independent research has identified an "intrinsic kill switch" baked into the model weights. The internal reasoning trace may formulate a complete technical response to politically sensitive topics, but the final output is blocked and replaced with a refusal message. These limitations cannot be bypassed through standard prompt engineering. For uncensored reasoning, consider community-modified versions such as Perplexity's R1-1776.

Hallucination and Security

Third-party evaluation by Artificial Analysis (April 2026) found V4-Pro and V4-Flash have hallucination rates of 94% and 96% respectively on omniscience tests. For factual tasks, always ground the model with Retrieval-Augmented Generation (RAG) using approved source documents. For production code generation, implement input/output filtering guardrails and maintain human-in-the-loop oversight.

Frequently Asked Questions