DeepSeek: R1

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DeepSeek R1 is DeepSeek's first-generation reasoning model released January 2025, trained via large-scale reinforcement learning to achieve performance comparable to OpenAI o1 on math, code, and reasoning tasks. It pioneered open-source reasoning capabilities with self-verification and reflection behaviors.

Context Window 164K

tokens

Max Output 16K

tokens

Input Cost $0.7

per million tokens

Output Cost $2.5

per million tokens

Release Date Jan 20, 2025

 

Code Example

Add AI to your app with the Puter.js AI API — no API keys or setup required.

// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms").then(response => {
    document.body.innerHTML = response.message.content;
});

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms").then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

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DeepSeek V4 Pro is a 1.6T-parameter Mixture-of-Experts model from DeepSeek with 49B parameters activated per token, supporting a 1M-token context window. It is positioned as the strongest open-weight model currently available. V4 Pro leads all open-source models in math, coding, and STEM reasoning. On LiveCodeBench it scores 93.5, ahead of Gemini 3.1 Pro (91.7) and Claude Opus 4.6 (88.8). Its Codeforces rating of 3206 also tops GPT-5.4 (3168). On agentic tool-use benchmarks like MCPAtlas, it reaches near-parity with Opus 4.6. DeepSeek acknowledges it trails GPT-5.4 and Gemini 3.1 Pro overall by roughly 3–6 months of frontier development. Priced at $1.74/M input and $3.48/M output — a fraction of comparable closed-source models — it's a strong pick for complex reasoning, agentic coding, and knowledge-intensive tasks.

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DeepSeek V3.2 is the December 2025 flagship model featuring DeepSeek Sparse Attention for efficiency and massive reinforcement learning post-training, achieving GPT-5-level performance. It's the first DeepSeek model to integrate thinking directly into tool-use and excels at agentic AI tasks.

Frequently Asked Questions

How do I use R1?

You can access R1 by DeepSeek through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.

Is R1 free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add R1 to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.

What is the pricing for R1?
R1 costs $0.7 per 1M input tokens and $2.5 per 1M output tokens.
Price per 1M tokens
Input$0.7
Output$2.5
Who created R1?

R1 was created by DeepSeek and released on Jan 20, 2025.

What is the context window of R1?

R1 supports a context window of 164K tokens. For reference, that is roughly equivalent to 328 pages of text.

What is the max output length of R1?

R1 can generate up to 16K tokens in a single response.

How does R1 perform on benchmarks?

R1 scores 27.1 on the Artificial Analysis Intelligence Index, outperforming 63% of tracked models. On coding, it scores 24.0 (outperforms 58% of models). On math, it scores 76.0 (outperforms 71% of models).

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the R1 API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

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