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Deepcoder 14B PreviewCode Like o3-mini

Try Deepcoder 14B PreviewAPI Documentation

Scale Code Reasoning

Long Context

64K Token Inference

Generalizes from 32K training to 64K contexts with 60.6% LiveCodeBench Pass@1.

RL Fine-Tuned

Beats Base 8%

Distributed RL from DeepSeek-R1-Distilled-Qwen-14B boosts coding accuracy to o3-mini level.

Efficient Training

Weeks Not Months

Overlong filtering and verl optimizations cut RL training time by 2x.

Examples

See what Deepcoder 14B Preview can create

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

LeetCode Sort

“Write a Python function to sort a list of integers using quicksort algorithm. Include time complexity analysis and handle edge cases like empty lists or duplicates. Output complete runnable code.”

Graph Traversal

“Implement BFS in Python for a directed graph represented as adjacency list. Find shortest path from node A to node Z. Add visualization using networkx if possible.”

Dynamic Programming

“Solve knapsack problem with weights [1,3,4,5], values [1,4,5,7], capacity 7 using memoization. Return max value and selected items as JSON.”

API Parser

“Parse OpenAPI spec YAML and generate Python client functions for all POST endpoints. Include error handling and authentication headers.”

For Developers

A few lines of code.
Code solves. API calls.

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 Deepcoder 14B Preview

Read the docs

Deepcoder 14B Preview is a code reasoning LLM fine-tuned from DeepSeek-R1-Distilled-Qwen-14B using distributed RL. It hits 60.6% Pass@1 on LiveCodeBench v5. Matches o3-mini with 14B parameters.

Deepcoder 14b preview API delivers 60.6% on LiveCodeBench at 64K context. Improves 8% over base model. Supports competitive coding and math tasks.

Overlong filtering enables 64K inference from 32K training. GRPO+ RL scales context effectively. Open-source with Docker and Ollama support.

Yes, Deepcoder 14B Preview alternative matches o3-mini (low) on LiveCodeBench at 60.6%. Open-source 14B model runs locally on 12GB GPU.

Deepcoder 14B Preview LLM available via Hugging Face, Together AI, Ollama, and Docker. Use Deepcoder 14b preview API for inference.

60.6% LiveCodeBench, 1936 Codeforces rating, 73.8% AIME2024. Excels in code generation, debugging, and long-context tasks.

Ready to create?

Start generating with Deepcoder 14B Preview on ModelsLab.

Try Deepcoder 14B PreviewAPI Documentation