--- library_name: transformers license: apache-2.0 base_model: - Qwen/Qwen3-4B-Instruct-2507 - Qwen/Qwen3-4B-Thinking-2507 - Neura-Tech-AI/Neuron-4B-Instruct pipeline_tag: text-generation language: - en - zh - hi - ar - ja - ko - fr - de - es - pt - it - ru - tr - vi - th - id - ms - bn - ur - ta - te - mr - gu - pa - fa new_version: Neura-Tech-AI/Neuron-6x4B-Instruct tags: - Neura Tech AI - Neuron - instruct - llm - transformer - mixture-of-experts - moe - multilingual - 24B - Qwen3 - Neuron-6x4B-Instruct - safetensors - conversational ---
Neuron

# Neuron-6x4B-Instruct > A next-generation open-source Mixture of Experts (MoE) language model developed by **Neura Tech AI**. ## Overview **Neuron-6x4B-Instruct** is a high-performance instruction-tuned Mixture of Experts (MoE) language model built upon the **Qwen3** architecture family. It features **6 routing experts**, each based on a 4B-scale expert design, providing improved expert specialization, efficient sparse computation, and enhanced multilingual capabilities. Neuron is designed to deliver strong performance across a wide range of AI workloads while maintaining efficient expert routing for inference. The model is developed entirely by: - **Neura Tech AI** Neuron focuses on delivering a capable multilingual AI assistant with strengths in: - High-efficiency sparse expert routing - Advanced logical reasoning - Software engineering and coding assistance - Mathematics and scientific problem solving - Agentic workflows and tool calling - Long-context document understanding - Multilingual communication across major world languages ## Model Architecture & Details Neuron-6x4B-Instruct utilizes a sparse Mixture of Experts architecture where tokens are dynamically routed to specialized experts during inference, improving efficiency without activating every parameter. - **Model Name:** Neuron-6x4B-Instruct - **Base Architecture:** Transformer Decoder (Sparse Mixture of Experts) - **Parameters:** ~24B Total Parameters - **Total Experts:** 6 Specialists - **Expert Size:** ~4 Billion Parameters per Expert - **Active Parameters:** ~4B Parameters Routed per Token (Dynamic Routing) - **Context Length:** 262,144 Tokens - **License:** Apache-2.0 ## Developer **Project:** Neuron **Developed by:** - Neura Tech AI ## Base Model Acknowledgment We sincerely thank the **Qwen Team** for releasing the Qwen3 model family under the Apache 2.0 License, which served as the architectural foundation for this project. ## Features - **6-Expert Sparse MoE Architecture:** Dynamic routing across six specialized experts for efficient inference. - **Instruction Optimized:** Tuned for helpful, structured, and accurate responses. - **Advanced Reasoning:** Strong performance on multi-step reasoning and analytical tasks. - **Coding Assistant:** Designed for software development, debugging, scripting, and code generation. - **Large Context Window:** Supports contexts up to 262K tokens for long documents and conversations. - **Tool Calling Ready:** Suitable for AI agents, structured outputs, JSON generation, and automation workflows. - **Multilingual:** Supports a broad range of major global languages. ## Performance > Benchmark results will be published after the official evaluation process is completed. | Category | Status | |----------|--------| | Knowledge | Coming Soon | | Reasoning | Coming Soon | | Coding | Coming Soon | | Mathematics | Coming Soon | | Alignment | Coming Soon | | Agent | Coming Soon | | Multilingual | Coming Soon | ## Intended Use Neuron-6x4B-Instruct is intended for: - Conversational AI - Coding assistants - AI agents - Research - Education - Content generation - Translation - Long-context document analysis - Software engineering workflows ## Disclaimer This model is intended for research and production use where appropriate. Outputs should be reviewed before being relied upon in safety-critical, legal, financial, or medical applications. --- # © 2026 Neura Tech AI. All rights reserved.