In 2025, DeepSeek has become one of the biggest names in AI. The Chinese company, founded in 2023 and backed by hedge fund High-Flyer, drew global attention by releasing models that sit close to OpenAI’s tools, but at a much lower cost. In January, DeepSeek-R1 launched with a clear focus on reasoning. It soon became the most downloaded free app, overtaking ChatGPT on app stores.
By mid-year, DeepSeek-V3 and DeepSeek-Coder-V2 helped cement their reputation for strong results and efficient use of resources. Later in 2025, DeepSeek-V3.2 and DeepSeek-V3.2-Speciale arrived with updates aimed at better long-context performance and agent-style work. These versions introduced features such as DeepSeek Sparse Attention to handle longer inputs more reliably, plus a reasoning-first approach for tool use. DeepSeek is available through the official site at chat.deepseek.com, with free access across web, mobile, and API options.
DeepSeek stands out for a few reasons: open-weight models (often under the MIT Licence), strong cost control (training on fewer resources), and solid performance in coding, maths, and reasoning. Developers use it to debug and build faster, analysts use it to sort and explain messy data. This guide shares practical ways to get better results, with a focus on coding and data analysis.
Getting Started with DeepSeek AI
To start, visit chat.deepseek.com or install the mobile app. Setup is simple. Users can create a free account and begin straight away. For advanced work, the API is OpenAI-compatible, which makes it easier to plug into existing apps and scripts.
DeepSeek’s key models include:
- DeepSeek-R1: Strong at logical reasoning and quick problem-solving.
- DeepSeek-V3.2: Built with reasoning first, supports tool use and long context.
- DeepSeek-Coder-V2: A Mixture-of-Experts model that supports 338 programming languages and 128K context.
A useful tip is to switch on Deep Think mode for harder tasks. It encourages step-by-step reasoning and often improves accuracy on complex prompts.
DeepSeek also supports file uploads in chat, including documents, code, and datasets. That makes it easier to analyse content without jumping between tools.
Writing Better Prompts for DeepSeek
DeepSeek works best when instructions are clear and well-structured. It tends to respond well to direct prompts, so users can say what they want without wrapping it in extra wording.
Basic prompt tips
- Be clear and detailed: Instead of “Write code for sorting”, use “Write a Python quicksort function, include comments and explain time complexity.”
- Assign a role: “You are an expert Python developer. Refactor this code to run faster.”
- Ask for step-by-step thinking: “Think step by step before answering.”
Advanced prompt approach
A simple structure that works well is PPFO (Purpose, Planning, Format, Output):
- Purpose: What the task is.
- Planning: The steps to take.
- Format: The layout to use (JSON, Markdown, bullet points).
- Output: The final deliverable.
Example coding prompt:
“Purpose: Act as a full-stack developer. Planning: Plan a React component for a to-do list. Format: Output in JSX with comments. Output: Provide the full component.”
Example for data analysis:
“Analyse this dataset step by step. First summarise key stats, then flag outliers, then suggest charts.”
DeepSeek can also cope with longer inputs. With Sparse Attention support in newer versions, users can paste large chunks of text, long reports, or bigger sections of code with fewer context issues.
Coding Tips: Move Faster in Daily Development
DeepSeek is often at its best with code tasks. DeepSeek-Coder-V2 is widely used for generating code, fixing bugs, and working across many languages.
Tip 1: Code generation and completion
Example prompt: “Generate a complete Flask API for user authentication, include JWT tokens and error handling.”
Once the first version is ready, a follow-up prompt can extend it: “Add unit tests using pytest.”
This approach keeps the work in small steps, which makes problems easier to spot and fix.
Tip 2: Debugging and refactoring
Users can upload broken code and ask: “Debug this script. It crashes on large inputs. Explain why, then provide a fixed version.”
For refactoring, a direct instruction helps: “Refactor this legacy JavaScript into modern ES6. Improve readability and performance.”
If the output changes behaviour, it helps to add: “Keep the same output, only change structure and performance.”
Tip 3: Multi-language support
DeepSeek supports 338 programming languages, which makes it useful for less common stacks.
Example: “Write a Rust binary tree implementation with traversal methods. Add simple tests.”
Tip 4: Building full projects in steps
A practical workflow is to build in phases:
- “Plan a full-stack MERN blog app. Provide a folder structure and key features.”
- “Implement the backend routes first, include validation and error handling.”
- “Add the front-end pages and connect them to the API.”
In API mode, function calling can also help when integrating tools, such as running code snippets or triggering internal actions.
The model’s strong coding performance is often linked to training on large volumes of code data (reported as 6T+ tokens), which helps it recognise patterns and common project layouts.
Data Analysis Tips: Turn Files into Useful Reports
DeepSeek can analyse uploaded files such as CSV, Excel, and JSON. It works well for quick summaries, cleaning steps, and turning numbers into clear notes.
Tip 1: Exploratory data analysis (EDA)
After uploading a dataset, a helpful prompt is: “Perform EDA on this file. Summarise key stats, check missing values, and describe the main distributions (describe plots if you can’t render them).”
A good follow-up: “Find correlations and suggest features that might help in a machine learning model.”
Tip 2: Cleaning and deeper analysis
For cleaning tasks: “Use pandas to clean this dataset. Remove duplicates, handle outliers, and normalise numeric columns.”
For business-style insight: “Analyse sales trends, then forecast next quarter with a simple linear regression. Provide code and explain the result.”
Tip 3: Visualisation support
Chat output is text-based, so it helps to request code plus an explanation:
“Write matplotlib code for a correlation heatmap, then explain what it suggests based on the data.”
This gives both the script and a plain-language readout.
Tip 4: Handling large inputs
DeepSeek can also process long logs and reports:
“Analyse this server log for errors and repeating patterns over time. Summarise the most common issues and when they happen.”
For stronger reasoning, combine it with Deep Think mode and ask for recommendations: “Think carefully and suggest business actions based on this customer data.”
Because DeepSeek is cost-efficient, it suits repeated analysis loops, especially when a team needs to test several ideas quickly.
Best Practices and Extra Tricks
Managing long threads
DeepSeek can keep context across longer chats, which helps with multi-step builds. A clear method is to keep a running checklist inside the chat, then ask it to update the checklist after each step.
Example: “Build a game step by step. Start with setup, then add one feature at a time. Keep a short list of what’s done and what’s next.”
Tool use and agent-style prompts
With V3.2, prompts can be written for tool use. For research-style tasks: “Research current AI trends and summarise them with sources.”
When sources matter, the prompt should state the rule clearly: “Only include claims that can be supported with sources.”
Saving money with the API
DeepSeek is known for low pricing. The text often quoted is around $0.55 per million input tokens. For repeated jobs, caching common prompts and results can reduce spend.
Reducing made-up answers
AI can still get facts wrong, so it helps to ask for limits:
“Use only the data provided. If something is missing, say what’s missing and stop.”
For coding, a useful check is: “Point out any assumptions you made.”
Integration ideas
DeepSeek can be used inside developer tools, such as VS Code via extensions, or through custom scripts that run prompts as part of a build or review process.
DeepSeek vs Other Tools: Why It’s Popular in 2025
DeepSeek often performs well against ChatGPT, Grok, and Claude in reasoning, maths, and coding, while staying free or open in many cases. It is also seen as less restricted than some rivals, though it may reflect certain viewpoints, so readers should use judgment and cross-check sensitive topics.
For multimodal tasks, it tends to trail tools like Gemini. For text, code, and data work, it has become a strong pick for many teams.
Conclusion: Keep Up with DeepSeek
DeepSeek has helped make strong AI tools easier to access in 2025. With clearer prompts, an iterative workflow, and smart use of its reasoning and long-context features, developers and analysts can get better results with less effort.
It is available to try at chat.deepseek.com, and its models can also be found via Hugging Face models.
