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What Is DeepSeek AI — And How Does It Compare To ChatGPT?
Last Updated:
Jan 8, 2026

What Is DeepSeek AI — And How Does It Compare To ChatGPT?

If you're wondering: what is DeepSeek AI, the answer is quite simple. DeepSeek AI is a Chinese AI research lab that builds large language models. The company released several models in late 2024 and early 2025 that compete directly with OpenAI's GPT-4 and Anthropic's Claude, but at a fraction of the operating cost.

The deepseek ai model lineup includes DeepSeek V3.2 (their main conversational model) and DeepSeek R1 (their reasoning-focused model that shows its thinking process). They've gained attention because their models perform comparably to much more expensive alternatives in benchmarks.

DeepSeek makes its models available through DeepSeek chat on their website, through API access, and via third-party platforms that integrate their technology. You can also chat with DeepSeek on Overchat AI.

Who Owns DeepSeek AI

DeepSeek is owned by High-Flyer Capital Management, a quantitative hedge fund based in Hangzhou, China. The fund's founder, Liang Wenfeng, started DeepSeek as an AI research division.

The company operates somewhat independently from typical chinese ai companies. They release their models with open weights, meaning researchers and developers can download and run them locally. Most Chinese tech giants like Baidu or Alibaba keep their models proprietary.

This open approach has made DeepSeek popular with the developer community. You can find their models on Hugging Face and run them on your own hardware if you have the resources.

DeepSeek AI Features

Deep Reasoning

The deepseek r2 (also called R1) shows you its thinking process before giving an answer. When you ask it a question, it generates a "reasoning trace" where you see the model working through the problem step by step.

For example, if you ask it to solve a math problem, you'll see it set up equations, check its work, catch mistakes, and revise its approach—all visible in the output before it gives you the final answer. This chain-of-thought reasoning makes it easier to spot where the model might be wrong and helps with debugging complex problems.

This feature is particularly useful for coding, mathematics, and logical reasoning tasks where you need to verify the AI's work.

Code Generation

DeepSeek V3.2 handles multiple programming languages including Python, JavaScript, C++, and Java. It can write complete functions, debug existing code, and refactor messy implementations.

The model was trained on a large corpus of code and can understand context across files. If you're working on a project, you can give it multiple files and it will maintain consistency with your existing codebase.

Long Context Window

deepseek v3 processes up to 128,000 tokens in a single conversation. That's roughly 90,000 words or about 300 pages of text. You can upload entire codebases, long documents, or multiple research papers and ask questions about all of them at once.

Multilingual Processing

The model handles Chinese and English particularly well since it was trained heavily on both languages. It also supports Japanese, Korean, Spanish, French, German, and other major languages.

How to Use DeepSeek AI

You can access DeepSeek through several methods depending on what you need.

Access DeepSeek on Overchat AI

The easiest option is through  Overchat AI:

  1. Go to Overchat AI
  2. Click the model selector dropdown
  3. Choose DeepSeek V3.2
  4. Start using it immediately

No signup required.

If you’re a developer, you can also use the DeepSeek API by generating API keys from their dashboard. The API follows OpenAI's format, so if you've integrated ChatGPT before, you can swap in DeepSeek endpoints with minimal code changes.

For advanced users, you can download the model weights and run DeepSeek locally. This requires significant hardware (multiple GPUs with at least 80GB of VRAM for the full model), but gives you complete control and privacy.

DeepSeek AI Pricing

DeepSeek undercuts most competitors. The free tier gives you full access to both deepseek chat models through their website.

There are rate limits, but for casual use you won't hit them. Most people can use DeepSeek without paying anything, unless you’re planning to use the API, which costs money. 

That being said, DeepSeek API also costs significantly less compared to ChatGPT or Claude. The table below compares API pricing between popular models:

Model Input (per 1M tokens) Output (per 1M tokens)
DeepSeek V3.2 $0.28 $0.39
DeepSeek R1 $0.55 $2.19
GPT-5.2 $1.75 $14.00
Gemini 3 Pro $2.00 $12.00
Claude Opus 4.5 $5.00 $25.00

DeepSeek V3.2 is dramatically cheaper than competing models. It costs 6x less than GPT-5.2, 7x less than Gemini 3 Pro, and 18x less than Claude Opus 4.5 for input tokens. Output tokens show similar savings.

Even DeepSeek R1 (the reasoning model) costs 3x less than GPT-5.2 and 6x less than Gemini 3 Pro. A million tokens is about 750,000 words. Unless you're processing massive amounts of text daily, costs stay low.

DeepSeek vs ChatGPT

The table below shows how DeepSeek and ChatGPT compare on current benchmarks:

Benchmark DeepSeek V3.2 DeepSeek R1 GPT-5.2 Thinking
AIME 2025 (Math) 96.0% 87.5% 100%
GPQA Diamond (Science) 59.1% 81.0% 92.4%
SWE-bench Verified (Coding) 73.1% 57.6% 80.0%
ARC-AGI-2 (Abstract Reasoning) 52.9%

Key Differences:

  • ChatGPT has a larger token context window. GPT-5.2 has a 400,000 token context window compared to DeepSeek's 128,000 tokens. For processing very large documents or codebases, GPT-5.2 holds an advantage.

  • GPT-5.2 supports multimodal inputs and outputs (images, vision tasks). DeepSeek V3.2 and R1 are text-only. If you need image analysis, GPT-5.2 is required.

  • DeepSeek's open weights mean you can run it locally if data privacy matters or if you want to fine-tune the model. GPT-5.2 only runs on OpenAI's servers.

  • GPT-5.2’s writing style tends to feel more natural. It's been heavily optimized for consumer chat experiences.

  • ChatGPT has more third-party integrations, better brand recognition, and a larger ecosystem. DeepSeek is growing fast among developers who prioritize cost efficiency and open-source flexibility.

DeepSeek Models Explained

DeepSeek V3.2

This is their main general-purpose model. It’s optimized for chats, writing simple code, analyzing text. This version includes DeepSeek Sparse Attention (DSA), which dramatically reduces costs for long-context processing. Use this for everyday tasks where you need reliable performance without showing the thinking process.

DeepSeek R1

This is the reasoning model. It shows its chain of thought and specializes in complex problem-solving. When you ask it a question, you see the model working through the problem step-by-step before it gives you the final answer. Use this when you need to verify the AI's logic or work through difficult technical problems like mathematics, competitive programming, or complex debugging.

DeepSeek V3.2-Speciale

This was a high-compute variant optimized for maximum performance on elite benchmarks. It achieved gold medal-level results on IMO, IOI, and ICPC competitions. This version was available through December 15, 2025.

Bottom Line

Key takeaways:

  • DeepSeek is an open-weights AI model similar to OpenAI's GPT.
  • The company is owned by High-Flyer Capital Management, a Chinese quantitative hedge fund.
  • DeepSeek V3.2 costs roughly 6-36x cheaper than GPT-5.2 to use through their API, depending on variant.
  • You can access DeepSeek through OverchatAI for free.
  • DeepSeek V3.2 scored 96.0% on AIME 2025 math benchmarks, matching GPT-5.2's performance at a fraction of the cost.
  • The main models are V3.2 for general use and R1 for reasoning tasks that show the model's thinking process.

DeepSeek proved that competitive AI models don't require massive budgets. They built V3 for roughly $6 million in compute costs — all the while, OpenAI spends hundreds of millions to train their models.

This efficiency comes from better training techniques and smart architectural improvements.

For users, it means more options. You're not locked into expensive API providers if you need powerful AI capabilities. Open weights mean you can modify and customize the model for specific needs.