Nex AGI: DeepSeek V3.1 Nex N1
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DeepSeek V3.1 Nex N1 is an agentic large language model post-trained by Nex AGI on top of DeepSeek's V3.1 base, built specifically for autonomous task execution, tool use, and multi-step workflows. It uses a 670B-parameter Mixture of Experts architecture with 37B activated parameters per token and supports a 131K context window.
The model is optimized for agent-oriented use cases: function calling, web search integration, code generation, and complex planning tasks. It performs well on agentic benchmarks including SWE-bench, GAIA 2, BFCL, and Terminal-Bench, with particular strength in practical coding and HTML generation.
Nex N1 is a strong pick for developers building AI agents, research assistants, or automated pipelines that need reliable tool use and multi-hop reasoning at an accessible price point.
Context Window 131K
tokens
Max Output 164K
tokens
Input Cost $0.14
per million tokens
Output Cost $0.5
per million tokens
Release Date Dec 8, 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>
More AI Models From Nex AGI
Nex N2 Mini
Nex N2 Mini is Nex AGI's smaller agentic model in the Nex N2 family, built on a Qwen3.5 base with 35B total parameters and 3B active per token, released open-source under Apache 2.0 alongside the larger Nex N2 Pro. It shares Nex N2 Pro's Agentic Thinking framework, pairing Adaptive Thinking, deciding on its own when and how deeply to reason, with Coherent Thinking, a consistent reasoning approach carried across general and agentic tasks. It supports a 262K context window and function calling. On benchmarks it scores 50.2 on SWE-Bench Pro, 60.7 on Terminal-Bench 2.1, 82.6 on GPQA Diamond, and 74.1 on BrowseComp, below Nex N2 Pro's 58.8, 75.3, and 90.7 on the same tests but at a fraction of the price. It fits developers who want Nex N2's agentic coding and tool-calling behavior for lighter, latency-sensitive, or budget-constrained workloads rather than maximum accuracy.
ChatNex N2 Pro
Nex N2 Pro is an agentic mixture-of-experts model from Nex AGI, built on a Qwen3.5 base with 397B total parameters and 17B active per token, released open-source under Apache 2.0 in June 2026. The model's Agentic Thinking framework closes the loop between planning, code implementation, environmental feedback, and iterative debugging — making it especially capable at long-horizon tasks. It supports function calling, structured outputs, vision inputs, and reasoning traces. Benchmark highlights include 75.3 on Terminal-Bench 2.1, 80.8 on SWE-Bench Verified, and 90.7 on GPQA Diamond. It is a strong fit for developers building coding agents, deep research pipelines, or multi-step automation that demands reliable tool use and a 262K context window.
Frequently Asked Questions
You can access DeepSeek V3.1 Nex N1 by Nex AGI 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.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add DeepSeek V3.1 Nex N1 to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.14 |
| Output | $0.5 |
DeepSeek V3.1 Nex N1 was created by Nex AGI and released on Dec 8, 2025.
DeepSeek V3.1 Nex N1 supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.
DeepSeek V3.1 Nex N1 can generate up to 164K tokens in a single response.
Yes — the DeepSeek V3.1 Nex N1 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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