ExaMind: Secure & Structured AI by AlphaExaAI
ExaMind is an advanced 7.62 billion parameter open-source conversational AI model developed by AlphaExaAI, built upon the Qwen2.5-Coder-7B architecture. It offers a substantial 32,768 token context window, extendable up to 128K with RoPE scaling, and is compatible with both CPU and GPU deployments.
Key Capabilities
- Advanced Programming: Excels in code generation, debugging, architecture design, and code review.
- Complex Problem Solving: Features multi-step logical reasoning and deep technical analysis.
- Security-First Design: Incorporates built-in prompt injection resistance (92% resistance rate) and strong identity enforcement, preventing impersonation.
- Multilingual Support: Optimized for English but supports all major world languages.
- Conversational AI: Provides natural, structured, and professional dialogue.
Benchmarks & Performance
ExaMind demonstrates strong performance across various domains:
- General Knowledge: Achieves 72.1% on MMLU (5-shot) and 94.8% on MMLU β World Religions (0-shot).
- Code Generation: Scores 79.3% on HumanEval (pass@1) and 71.8% on MBPP (pass@1).
- Math & Reasoning: Attains 82.4% on GSM8K (8-shot CoT).
Training & Architecture
The model was developed using a multi-stage training pipeline, including Supervised Fine-Tuning (SFT) on curated 2026 datasets, LoRA adaptation, and dedicated stages for identity enforcement and security alignment. It utilizes a Transformer architecture with 28 layers and Grouped-Query Attention (GQA) with 4 KV heads.