Rnj 1 Instruct

Essential AI

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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Technical Specifications

Context Window

32,768 tokens

Max Output

32,768 tokens

Pricing

Token Costs (per 1M tokens)

Cache Miss Input

$0.15

Non-Reasoning Output

$0.15

Legacy

Made legacy on

Reason

EssentialAI model; limited availability

Recommended Replacement

Qwen3.6 Plus