Rnj 1 Instruct

essentialai

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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Example Use Cases

Programming or math reasoning

Agentic coding workflow

Scientific reasoning on a budget

Technical Specifications

Context Window

32,768 tokens

Max Output

32,768 tokens

Cache Miss Cost

$0.15 per 1M tokens

Non-Reasoning Cost

$0.15 per 1M tokens

Web Search Cost

$15 per 1K calls

Code Execution Cost

$0.19 per 1K calls

⚠️ Legacy

Made legacy on

Reason

Untested

Recommended Replacement

Qwen3.5 Plus