DeepSeek in 2026: what it is, whether it’s worth it, and how it compares

DeepSeek in 2026: what it is, whether it’s worth it, and how it compares

N Equipo NodoAI
4 min read

DeepSeek went from being an unknown name to shaking the entire AI industry. Its reasoning model matches the best from OpenAI at a fraction of the cost — and it’s open source. Here’s what it is, what models it has, how to use it, where it wins and loses against ChatGPT, Claude and Gemini, and the privacy issue nobody should ignore.

What happened

In early 2025, a nearly unknown Chinese lab released DeepSeek-R1, a reasoning model that competed with OpenAI’s best at a fraction of the training cost. The impact was so big it moved the stock markets and forced big tech to rethink pricing. By 2026, DeepSeek is a first-tier player.

Its play is clear: powerful models, open (downloadable weights) and cheap. The exact opposite of OpenAI’s closed strategy.

What DeepSeek is, exactly

DeepSeek is both an AI lab and a model family. The two that matter:

  • DeepSeek-V3: generalist model (GPT-style), fast and very capable for chat, code and writing.
  • DeepSeek-R1: reasoning model that “thinks” step by step before answering, OpenAI o1/o3 style. Shines in math, logic and programming.

Use it free on its web and app, via low-cost API, or download the weights and run it yourself.

Why it matters

Three reasons make it a turning point:

  • Price: its API costs a fraction of OpenAI or Anthropic for similar capability. With many calls, savings are huge.
  • Open: by publishing weights, anyone can audit, fine-tune and run it without depending on a single company.
  • Proved it’s possible: broke the idea that only billions of dollars produce a frontier model. That democratizes AI.

How to use it

Four ways, from easiest to most technical:

  • Web and app: go to chat.deepseek.com or install the app. Free, similar to ChatGPT. Toggle the reasoning mode (R1) for hard problems.
  • API: for developers; it’s OpenAI-format compatible, so migrating is almost as simple as changing the URL and key.
  • Local: download the models from Hugging Face and run them with Ollama or vLLM. There are small distilled versions that run on a powerful laptop.
  • Via third parties: many platforms (OpenRouter and similar) offer it with no setup needed.

DeepSeek vs. ChatGPT, Claude and Gemini

In reasoning and math: R1 plays in the o1/o3 and Claude league. For logic problems and complex code, it’s right there.

In chat and writing: very good, although ChatGPT and Claude still feel a bit more polished and natural in English.

In price: DeepSeek wins by a mile. That’s its biggest edge.

In ecosystem: ChatGPT and Gemini have more mature apps, integrations and multimodality. DeepSeek lags here.

The privacy catch

DeepSeek is a Chinese company and, if you use their official web or API, your data is processed on their servers under Chinese law. For personal use or experiments, fine. But do not put sensitive, confidential or client data in the official version.

The good news: because it’s open, you can run it on your own server (or a European one) and your data never leaves your control. That’s the recommended route for companies.

Limitations

  • Censorship: the official version avoids topics politically sensitive in China.
  • English nuance: very competent, but sometimes less natural than ChatGPT or Claude.
  • Multimodality: behind on image, voice and video vs. the majors.
  • Support: less mature ecosystem and docs than OpenAI’s.

Our verdict

DeepSeek is the best news for anyone who wants AI power without paying premium prices. For reasoning and code at a low cost, it’s among the best out there. For sensitive work, use it only locally. And if you value the most polished English experience and a full ecosystem, ChatGPT or Claude still have an edge.

It’s not a “ChatGPT killer”; it’s something more interesting: proof that frontier AI is no longer the exclusive domain of three American companies.

Practical recommendation: try it free on their web for non-sensitive tasks and compare it with your usual AI on a real code or logic problem. If you make many API calls, calculate the savings — you’ll likely be surprised.

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