ghayma-genai-docs/Models.md

Ghaymah GenAI: Available Models

This page provides an overview of the powerful AI models available through the Ghaymah GenAI API. Each model is designed with a unique architecture and set of strengths, allowing you to choose the best tool for your specific application.

Model Descriptions

• QwQ-32B: A reasoning model from the Qwen series, excelling in thinking and complex problem-solving. It is particularly strong in mathematics and programming tasks, making it a great choice for technical applications.

• DeepSeek-V3-0324: A robust Mixture-of-Experts (MoE) model. This architecture activates a smaller number of parameters per token, making it efficient while delivering excellent performance in reasoning, mathematics, and code generation.

• gemma-3-4b-it: A lightweight, state-of-the-art model designed for efficiency and versatility. It is highly capable of handling general-purpose tasks and is ideal for applications where speed and a smaller footprint are priorities.

• Qwen3-32B: The latest model from the Qwen series, known for its exceptional reasoning and coding abilities. It also offers extensive multilingual support, making it a top choice for global applications.

• GLM-4.5-Air: A reasoning model from the GLM series. It is a more compact version of its flagship counterpart, offering a balance of enhanced logical and mathematical capabilities with a more efficient resource footprint. It's particularly strong in tool-calling and agentic tasks.

• Kimi-K2-Instruct: A large AI model developed by Moonshot AI. It is highly praised for its ability to understand and excel in long-context conversations and is also a strong performer in multilingual support.

Model Comparison

To help you select the most suitable model, refer to the table below, which compares each model's key strengths and ideal use cases.

Model	Primary Strengths	Best Suited For	Real-World Application Examples
QwQ-32B	Strong reasoning, math, and programming capabilities. Efficient.	Technical problem-solving, code generation, and mathematical computations.	A coding assistant that auto-completes code, generates complex functions, or debugs logical errors in a program. An AI tutor for a STEM education platform.
DeepSeek-V3-0324	Efficient Mixture-of-Experts (MoE) architecture. Excellent performance in reasoning and code.	Balanced performance for general-purpose use, especially in coding and logical tasks.	A general-purpose chatbot for a tech support website that can answer a wide range of questions, from simple queries to more complex coding problems.
gemma-3-4b-it	Lightweight and fast. Excellent for general text generation and instruction following.	Resource-constrained environments, quick chatbots, and simple text-based applications.	A mobile app chatbot that provides quick, real-time responses. An internal tool for generating short summaries of emails or reports.
Qwen3-32B	Exceptional reasoning and coding abilities. Strong multilingual support.	Applications requiring sophisticated logic, complex coding, or global language support.	A multilingual customer support system that handles inquiries in various languages. A software development platform that can explain complex codebases in multiple languages.
GLM-4.5-Air	Enhanced logical and mathematical reasoning. Excellent at tool-calling and agentic workflows.	Building AI agents, automating multi-step tasks, and applications that require external tool integration.	An AI agent that can book flights for a user by calling an external flight-booking API, check the weather, and send a confirmation email. A data analysis tool that can run multiple commands and generate a comprehensive report.
Kimi-K2-Instruct	Outstanding long-context understanding. Robust multilingual and conversational abilities.	Chatbots, summarization of long documents, and applications requiring in-depth conversational recall.	A chatbot for legal document review that can answer questions about a 100-page contract. A meeting summarization tool that generates a detailed recap of a long transcript.