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cyankiwi rnj-1-instruct-AWQ-8bit · Hugging Face Rnj-1 is a family of 8B parameter open-weight, dense models trained from scratch by Essential AI, optimized for code and STEM with capabilities on par with SOTA open-weight models These models perform well across a range of programming languages and boast strong agentic capabilities (e g , inside agentic frameworks like mini-SWE-agent), while also excelling at tool-calling They additionally
Rnj-1 Instruct API | Together AI Introducing Rnj-1 Instruct Rnj-1 Instruct is Essential AI's elite 8B agentic coding model, delivering world-class software engineering capabilities that rival models 10x its size With 20 8% on SWE-bench Verified, exceptional tool use (62 2% BFCL), and a 32K context window, it excels at autonomous coding agents, iterative problem-solving, and multi-step technical workflows Released under
Transformer co-creator Vaswani unveils high-performance Rnj-1 coding model Essential AI's new open-source model, Rnj-1, outperforms significantly larger competitors on the "SWE-bench Verified" test This benchmark is considered particularly challenging because it evaluates an AI's ability to independently solve real-world programming problems Despite being a compact model
EssentialAI: Rnj 1 Instruct – Quickstart | OpenRouter Sample code and API for 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 scientific reasoning The model demonstrates strong performance across multiple programming languages, tool-use workflows, and agentic execution environments (e g , mini-SWE-agent)
Essential AI announces Rnj-1, - GIGAZINE(ギガジン) Essential AI, an open-source AI company, has announced the Rnj-1 language model Rnj-1 is designed to handle long contexts of up to 32,000 tokens with 8 billion parameters, and has demonstrated
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