DeepSeek: DeepSeek V3.1 Terminus
Reason Smarter, Faster
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.
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
import requestsresponse = requests.post("https://modelslab.com/api/v7/llm/chat/completions",json={"key": "YOUR_API_KEY","prompt": "","model_id": ""})print(response.json())
Ready to create?
Start generating with DeepSeek: DeepSeek V3.1 Terminus on ModelsLab.