DeepSeek¶
What it is¶
DeepSeek is an AI research company that provides powerful open-weight and API-based models, particularly strong in coding and mathematics.
What problem it solves¶
Provides extremely high-performance LLMs (rivaling GPT-4/Claude 3.5) at a significantly lower cost point, making high-volume agentic loops more affordable.
Where it fits in the stack¶
LLM / Reasoning Engine. A cost-effective alternative for coding agents and complex reasoning tasks.
Architecture overview¶
Available via their own API (DeepSeek Platform) or can be self-hosted using the open-weight versions (DeepSeek-V3, DeepSeek-Coder-V2).
Typical workflows¶
- Massive Refactoring: Using high-performance models for large-scale code changes without the high cost of OpenAI/Anthropic.
- Math/Logic Tasks: Leveraging DeepSeek's strong performance in logic-heavy domains.
- Cheap Agentic Exploration: Running agents in "discovery" modes where many API calls are expected.
Strengths¶
- Incredible Price/Performance: Often 1/10th or less of the cost of competitors for similar performance.
- Coding Performance: DeepSeek-Coder series is top-tier.
- Open Weights: Allows for self-hosting on high-end hardware.
Limitations¶
- Region/Availability: Can sometimes experience higher latency or downtime depending on API region.
- Model Bias: May have different behavioral nuances compared to Western-developed models.
When to use it¶
- When cost is a major factor in scaling agentic workflows.
- For specialized coding tasks where DeepSeek-Coder excels.
- When you want to experiment with high-end reasoning without a large budget.
When not to use it¶
- If your security policy restricts data flow to certain regions/providers.
- When absolute maximum reliability (SLA) is required (OpenAI/Anthropic are generally more stable).
Security considerations¶
- API Privacy: Review their data handling and privacy policy.
- Key Management: Use standard secret management practices.