DeepSeek API Quick Start Guide

DeepSeek provides an API compatible with OpenAI and Anthropic formats, allowing for easy integration using existing SDKs. The guide outlines the necessary base URLs, model names, and authentication steps required to begin making calls. It includes specific code examples for multiple programming environments to demonstrate how to invoke chat completions with advanced reasoning features.

Key Points

• DeepSeek API is fully compatible with OpenAI and Anthropic SDKs, requiring only a change to the base URL and API key.
• The primary models available are deepseek-v4-flash and deepseek-v4-pro, with legacy names scheduled for deprecation in 2026.
• Developers can enable advanced features such as 'thinking' mode and adjust 'reasoning_effort' within the API request body.
• The guide provides ready-to-use code snippets for curl, Python (OpenAI SDK), and Node.js (OpenAI SDK).
• Streaming responses are supported by setting the stream parameter to true in the chat completion request.

Sentiment

The community is broadly impressed by DeepSeek V4, particularly its pricing and the Flash model's speed. However, there is notable skepticism about whether it truly matches frontier proprietary models, and the Pro model's current reliability issues temper enthusiasm. The discussion is heavily colored by geopolitical framing, with many commenters using V4 as evidence for their views on US-China competition, AI economics, and open vs closed models.

In Agreement

• V4 Pro produces remarkably impressive mathematical proofs at the PhD research level, performing comparably to top Gemini and GPT models
• DeepSeek's API documentation is concise, developer-friendly, and superior to the bloated docs from Western labs
• The low pricing proves that frontier-quality inference can be delivered profitably without the markups Western labs charge
• V4 Flash is exceptionally fast and cost-effective, particularly strong in agentic and iterative workflows
• Open-weight models from Chinese labs are rapidly closing the gap with proprietary Western frontier models
• The bitwise deterministic inference implementation is a notable technical achievement that other labs haven't matched

Opposed

• V4 Pro is too slow, rate-limited, and unreliable to be practically useful compared to established frontier models
• Chinese models benchmark well but never quite keep pace with true state-of-the-art from Anthropic, OpenAI, or Google
• The claim that V4 runs entirely on Huawei chips was unsubstantiated and debunked by the community
• Minor grammar and spelling errors in documentation signal lack of attention to detail
• DeepSeek's pricing may be subsidized by Chinese state support rather than reflecting true economics
• Privacy concerns around Chinese AI services are legitimate and shouldn't be dismissed