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Frequently Asked Questions

What is the difference between DeepSeek-V4 and DeepSeek-R1?
DeepSeek-R1 is a specialized reasoning model designed for complex multi-step logic, mathematical problem-solving, and analytical tasks. DeepSeek-V4 is a general-purpose flagship model optimized for speed, agent workflows, and supports a large 256K token context window.

Is DeepSeek-V4 open source?
DeepSeek follows an open-weight model, meaning the model parameters are publicly available for download and local hosting. However, the training data and training pipeline remain proprietary.

What is the difference between DeepSeek V4-Flash and V4-Pro?
DeepSeek V4-Pro is the flagship model with approximately 1.6 trillion parameters, built for maximum performance and advanced tasks. V4-Flash is a lighter version with around 284 billion parameters, optimized for faster responses and lower cost.

Where is data stored when using DeepSeek?
When using the official platform or API, data is processed in DeepSeek’s data centers in China. Users can host models locally for greater control and privacy.

Does DeepSeek use chats for training?
Data from the web interface and API may be used to improve models, depending on current policies. Enterprise and self-hosted deployments may have different data handling terms.

Why is DeepSeek cheaper than competitors?
DeepSeek uses architectures like Mixture-of-Experts (MoE) and Multi-Head Latent Attention (MLA), which reduce computational costs while maintaining strong performance.

How can I get a DeepSeek API key and are there limits?
API keys can be generated through the DeepSeek Open Platform. Rate limits are dynamic and depend on server load and usage history.

Why do “Server Busy” errors occur?
These errors usually happen during periods of high demand, especially after new model releases. Using third-party providers or local deployment can help reduce interruptions.

Can DeepSeek handle large files or long codebases?
Yes, DeepSeek-V4 supports up to 256K tokens, enabling it to process large documents, books, and complex codebases.

What are the hardware requirements for running DeepSeek locally?
Smaller models like 7B or 14B can run on consumer GPUs, while full-scale models like V4-Pro require enterprise-grade GPU clusters with high VRAM.

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