Essentialai rnj-1-instruct

Rnj-1 is an 8B-parameter, dense, open-weight model family developed by Essential AI and trained from scratch with a focus on programming, math, and sc

Rnj-1 is an 8B-parameter, dense, open-weight model family developed by Essential AI and trained from scratch with a focus on programming, math, and scientific reasoning. The model demonstrates strong performance across multiple programming languages, tool-use workflows, and agentic execution environments (e.g., mini-SWE-agent).

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Why It Looks Great

• Large Language Model architecture for efficient processing
• 32768 context window for long document handling
• Competitive pricing at $0.1/$0.1 per million tokens

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Key Features

• Context Window: 32768 tokens
• Max Output: N/A tokens
• Vision: Supported
• Function Calling: Supported

Specifications

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Pricing

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How to Use

1. Write your prompt — describe the task, provide context, and specify desired output format.
2. Submit — the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: essentialai/rnj-1-instruct

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API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="essentialai/rnj-1-instruct",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "essentialai/rnj-1-instruct",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

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Notes

• Model: essentialai/rnj-1-instruct
• Provider: Essentialai