--- title: DeepSeek V3.1 Terminus — Advanced Reasoning LLM | Model... description: Access DeepSeek: DeepSeek V3.1 Terminus API for hybrid thinking, agent tools, and 128k context. Generate reliable outputs via ModelsLab endpoints now. url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/deepseek-deepseek-v31-terminus canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/deepseek-deepseek-v31-terminus type: website component: Seo/ModelPage generated_at: 2026-05-13T10:35:10.896706Z --- Available now on ModelsLab · Language Model DeepSeek: DeepSeek V3.1 Terminus Reason Smarter, Faster --- [Try DeepSeek: DeepSeek V3.1 Terminus](/models/open_router/deepseek-deepseek-v3.1-terminus) [API Documentation](https://docs.modelslab.com) Hybrid Modes, Strong Agents --- Dual Inference ### Think or Direct Mode Switch between chain-of-thought reasoning and fast non-thinking responses in DeepSeek: DeepSeek V3.1 Terminus. Agent Optimized ### Code, Search Tools DeepSeek: DeepSeek V3.1 Terminus boosts code agent and search agent with structured outputs and function calls. Context Mastered ### 128k Token Window Handles long prompts and code blocks reliably in deepseek deepseek v3 1 terminus model. Examples See what DeepSeek: DeepSeek V3.1 Terminus can create --- Copy any prompt below and try it yourself in the [playground](/models/open_router/deepseek-deepseek-v3.1-terminus). Code Review “Review this Python function for efficiency and bugs: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2). Suggest optimizations and rewrite with memoization.” SQL Query “Write an optimized SQL query to find top 10 customers by total spend from orders table joined with customers, filtering last year, using window functions.” JSON Schema “Generate JSON schema for user profile with fields: name (string), age (integer 0-120), email (string format), preferences (array of strings). Include validation rules.” Algorithm Explain “Explain Dijkstra's shortest path algorithm step-by-step with pseudocode example for graph with nodes A-B-C, edges A-B:5, A-C:2, B-C:1. Compute paths from A.” For Developers A few lines of code. Reasoning LLM. One Call. --- ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed. - **Serverless:** scales to zero, scales to millions - **Pay per token,** no minimums - **Python and JavaScript SDKs,** plus REST API [API Documentation ](https://docs.modelslab.com) PythonJavaScriptcURL Copy ```

import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

``` FAQ Common questions about DeepSeek: DeepSeek V3.1 Terminus --- [Read the docs ](https://docs.modelslab.com) ### What is DeepSeek: DeepSeek V3.1 Terminus? DeepSeek V3.1 Terminus updates V3.1 with language consistency fixes and agent improvements. It supports hybrid think/non-think modes. Available via API on ModelsLab. ### How does deepseek deepseek v3 1 terminus API work? Send messages array and model ID 'deepseek-ai/DeepSeek-V3.1-Terminus' in requests. Supports temperature, top_p, penalties for control. Use structured JSON outputs. ### What context length for DeepSeek: DeepSeek V3.1 Terminus model? Features 128k-130k token context window. Handles long prompts and code blocks smoothly. Optimized for extended training phases. ### Is DeepSeek: DeepSeek V3.1 Terminus alternative to other LLMs? Outperforms on benchmarks like GPQA-Diamond (80.7) and BrowseComp (38.5). Strong in coding (LiveCodeBench 74.9) and reasoning. Cost-effective via OpenRouter pricing. ### DeepSeek: DeepSeek V3.1 Terminus LLM agent capabilities? Enhanced code and search agents post-training. Supports tool calling, function selection, and multi-step tasks. Faster thinking than prior models. ### Access DeepSeek deepseek v3 1 terminus api here? Integrate via ModelsLab LLM endpoints with standard OpenAI-compatible schema. Free tier available; pay per token usage. Open-source weights on Hugging Face. Ready to create? --- Start generating with DeepSeek: DeepSeek V3.1 Terminus on ModelsLab. [Try DeepSeek: DeepSeek V3.1 Terminus](/models/open_router/deepseek-deepseek-v3.1-terminus) [API Documentation](https://docs.modelslab.com) --- *This markdown version is optimized for AI agents and LLMs.* **Links:** - [Website](https://modelslab.com) - [API Documentation](https://docs.modelslab.com) - [Blog](https://modelslab.com/blog) --- *Generated by ModelsLab - 2026-05-13*