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DeepSeek: R1 0528DeepSeek: R1 0528 Reasoning

Try DeepSeek: R1 0528API Documentation

Reason Deeper. Code Smarter.

Step-by-Step Reasoning

Simplified Thinking Mode

Access chain-of-thought reasoning without prompt engineering or thinking tokens.

SOTA Benchmarks

Math and Coding Mastery

Matches O3 and Gemini 2.5 Pro on AIME 2024, LiveCodeBench, and logic tasks.

Agentic Ready

Function Calling Support

Enables JSON output and tool use for RAG, agents, and enterprise apps.

Examples

See what DeepSeek: R1 0528 can create

Copy any prompt below and try it yourself in the playground.

Math Proof

“Prove the Pythagorean theorem step-by-step, showing all logical deductions and geometric reasoning without diagrams.”

Code Debugger

“Debug this Python function for sorting linked lists: def merge_sort(head): ... Explain errors and provide fixed code with tests.”

Logic Puzzle

“Solve this riddle: Three logicians know at least one has a dirty face. None leave. Explain their reasoning chain to deduce clean faces.”

Algorithm Design

“Design an efficient algorithm for the traveling salesman problem using dynamic programming. Include pseudocode, time complexity, and example.”

For Developers

A few lines of code.
Reasoning via API. 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 
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: R1 0528

Read the docs

DeepSeek: R1 0528 is an upgraded LLM from DeepSeek AI with enhanced reasoning depth. It uses more compute and post-training optimizations for math, coding, and logic. Performance nears O3 and Gemini 2.5 Pro.

It simplifies access to thinking mode without prepending tokens. Chain-of-thought distillation boosts small models like Qwen3-8B. Reduced hallucinations aid reliable outputs.

Optimized for complex reasoning, programming, math benchmarks like AIME 2024. Supports function calling, JSON output, and agentic systems. Strong in RAG and conversational AI.

Yes, weights available on Hugging Face. Run locally for data control and no per-token costs. Distilled versions exist for efficiency on 24GB GPUs.

Yes, enhanced function calling and JSON mode. Ideal for vibe coding and enterprise retrieval. No API usage changes needed.

Integrate via standard LLM endpoints. Enable thinking mode per docs for step-by-step outputs. Test on platforms like Fireworks or OpenRouter.

Ready to create?

Start generating with DeepSeek: R1 0528 on ModelsLab.

Try DeepSeek: R1 0528API Documentation