DeepSeek V3 Review: A Seasoned Developer's Insights After 30 Hours of Coding
Welcome to this in-depth review of DeepSeek V3, where we explore whether this language model (LLM) can become a developer's new go-to tool. After spending 30 hours coding with DeepSeek V3 as the primary LLM, I am excited to share my insights and experiences. This article delves into the various aspects of using DeepSeek V3, highlighting its strengths and areas for improvement.
Introduction to DeepSeek V3
DeepSeek V3 is the latest iteration of a powerful AI coding assistant designed to streamline development tasks. From code cleanup to API development, and even architectural planning, DeepSeek V3 claims to offer superior performance. But does it live up to the hype? Let's find out.
In-depth Review and Usage
Coding and Cleanup
A significant portion of my time with DeepSeek V3 was spent on coding, constituting about 60% of my usage. I primarily work with Python and AWS technologies, including serverless functions, CDK deployments, and PostgreSQL scripts. One of the standout features of DeepSeek V3 is its proficiency in code cleanup.
I utilized it to transform a prototype feature into production-ready code. This involved removing unnecessary 'cruft'—placeholders and redundant functions typical in prototype development. For instance, I provided a file with over 1000 lines of code, and DeepSeek V3 reduced it to 415 lines in a single attempt. The only mistake was the removal of two tabs that were non-functional but desired for future use. Upon specifying to retain them, the tool corrected this in the subsequent attempt.
Writing and Architecture
While my usage was less extensive in writing, I did employ DeepSeek V3 for marketing content and e-commerce wording suggestions. Additionally, it proved invaluable for architectural planning. I used it to generate diagrams and data models for new features, where it even suggested improvements that I eventually incorporated.
API Development
DeepSeek V3 excelled in API development, providing accurate and comprehensive code based on examples I provided. It consistently covered necessary elements, including authentication, which was often missed by other models like Claude.
Side Projects and Prototyping
In a side project involving a chess game with LLM-controlled players, DeepSeek V3 quickly generated a working prototype. Although the LLM's chess-playing capabilities were lackluster, the speed and ease of prototyping were impressive.
Comparison with Other LLMs
DeepThinking and Perplexity
I experimented with DeepSeek V3's reasoning models but found them less effective for coding compared to regular prompt searches. While perplexity remains my primary search tool, DeepSeek V3 shows potential to replace it.
Context Limits and Project Management
Unlike Claude, which often hits context limits, I did not encounter this issue with DeepSeek V3. However, I am adept at starting new chats when necessary. Project management features in Claude, specifically Projects, were missed, but the flow and usability of DeepSeek V3 compensated for this.
Considerations and Recommendations
Security and Data Sensitivity
As DeepSeek is a Chinese company, there are concerns about data privacy. It is crucial never to upload sensitive information, proprietary code, or API keys to cloud-based AI. While I do not foresee significant risks with non-sensitive code and UI, caution is advised.
Open Source and Performance
DeepSeek V3 is fully open source, offering the possibility to run it locally. However, this requires substantial computational resources, which might not be feasible for most users.
Conclusion
DeepSeek V3 has proven to be an exceptional AI coding assistant. Its performance in code cleanup, API development, and architectural planning is commendable. While there are areas for improvement, such as handling context limits and certain project management features, its strengths make it a valuable tool for developers.
For the foreseeable future, DeepSeek V3 will remain my primary LLM, with other models like Gemini Flash and Ancta serving as backups when needed. I recommend DeepSeek V3 to developers seeking a robust and efficient coding assistant, but always with caution regarding data sensitivity.
FAQ
- How does DeepSeek V3 handle code cleanup?
DeepSeek V3 efficiently reduces code clutter by removing unnecessary elements like placeholders and redundant functions, significantly streamlining the codebase.
- Can DeepSeek V3 manage API development?
Yes, it can manage API development effectively, covering necessary elements such as authentication and data models based on provided examples.
- What are the main concerns when using DeepSeek V3?
The primary concerns are related to data privacy, especially given that DeepSeek is a Chinese company, and ensuring that no sensitive information is uploaded to the cloud.
- How does DeepSeek V3 compare to other LLMs like Claude and Perplexity?
DeepSeek V3 offers superior performance in code-related tasks compared to Claude and shows potential to replace Perplexity as a primary search tool.
Thank you for reading this review. I invite you to share your experiences and thoughts on DeepSeek V3 in the comments below. If you found this article helpful, please subscribe and like for more content like this.
