Criteria for Compare LLMs | Slide


criteria-to-compare-llms



Criteria for Comparing Different Large Language Models

When evaluating and comparing different large language models, several key factors need to be taken into consideration. These factors play a crucial role in determining the performance and suitability of a language model for specific tasks. Below is a breakdown of the criteria used to compare large language models:

Factors Description
Size of Model The size of the model refers to the number of parameters it contains. Larger models tend to have more parameters, which can potentially lead to better performance but may also require more computational resources.
Accuracy of Task The accuracy of the task measures how well the language model performs on specific tasks such as text generation, translation, or sentiment analysis. Models with higher accuracy are generally preferred.
Ability to Fine-Tune Model The ability to fine-tune a model allows users to adapt the pre-trained model to specific tasks or domains. Models that are easily fine-tuned are more versatile and can be customized for various applications.
Training Data Used The training data used to train the language model greatly impacts its performance. Models trained on diverse and extensive datasets tend to have a broader understanding of language and context.
Architecture Used The architecture of a language model, such as Transformer, LSTM, or BERT, influences its capabilities and performance. Different architectures have unique strengths and weaknesses that should be considered.
Other Factors Additional factors to consider include inference speed, memory requirements, energy efficiency, and support for different languages. These factors can affect the practicality and usability of a language model in real-world applications.

Blog


100K-tokens    Agenda    Ai-assistant-architecture    Ai-assistant-building-blocks    Ai-assistant-custom-model    Ai-assistant-evaluation-metric    Ai-assistant-finetune-model    Ai-assistant-on-your-data    Ai-assistant-tech-stack    Ai-assistant-wrapper   

Dataknobs Blog

10 Use Cases Built

10 Use Cases Built By Dataknobs

Dataknobs has developed a wide range of products and solutions powered by Generative AI (GenAI), Agent AI, and traditional AI to address diverse industry needs. These solutions span finance, healthcare, real estate, e-commerce, and more. Click on to see in-depth look at these use cases - Stocks Earning Call Analysis, Ecommerce Analysis with GenAI, Financial Planner AI Assistant, Kreatebots, Kreate Websites, Kreate CMS, Travel Agent Website, Real Estate Agent etc.

AI Agent for Business Analysis

Analyze reports, dashboard and determine To-do

DataKnobs has built an AI Agent for structured data analysis that extracts meaningful insights from diverse datasets such as e-commerce metrics, sales/revenue reports, and sports scorecards. The agent ingests structured data from sources like CSV files, SQL databases, and APIs, automatically detecting schemas and relationships while standardizing formats. Using statistical analysis, anomaly detection, and AI-driven forecasting, it identifies trends, correlations, and outliers, providing insights such as sales fluctuations, revenue leaks, and performance metrics.

AI Agent Tutorial

Agent AI Tutorial

Here are slides and AI Agent Tutorial. Agentic AI refers to AI systems that can autonomously perceive, reason, and take actions to achieve specific goals without constant human intervention. These AI agents use techniques like reinforcement learning, planning, and memory to adapt and make decisions in dynamic environments. They are commonly used in automation, robotics, virtual assistants, and decision-making systems.

Build Dataproducts

How Dataknobs help in building data products

Building data products using Generative AI (GenAI) and Agentic AI enhances automation, intelligence, and adaptability in data-driven applications. GenAI can generate structured and unstructured data, automate content creation, enrich datasets, and synthesize insights from large volumes of information. This helps in scenarios such as automated report generation, anomaly detection, and predictive modeling.

KreateHub

Create New knowledge with Prompt library

At its core, KreateHub is designed to enable creation of new data and the generation of insights from existing datasets. It acts as a bridge between raw data and meaningful outcomes, providing the tools necessary for organizations to experiment, analyze, and optimize their data processes.

Build Budget Plan for GenAI

CIO Guide to create GenAI Budget for 2025

CIOs and CTOs can apply GenAI in IT Systems. The guide here describe scenarios and solutions for IT system, tech stack, GenAI cost and how to allocate budget. Once CIO and CTO can apply this to IT system, it can be extended for business use cases across company.

RAG For Unstructred and Structred Data

RAG Use Cases and Implementation

Here are several value propositions for Retrieval-Augmented Generation (RAG) across different contexts: Unstructred Data, Structred Data, Guardrails.

Why knobs matter

Knobs are levers using which you manage output

See Drivetrain appproach for building data product, AI product. It has 4 steps and levers are key to success. Knobs are abstract mechanism on input that you can control.

Our Products

KreateBots

  • Pre built front end that you can configure
  • Pre built Admin App to manage chatbot
  • Prompt management UI
  • Personalization app
  • Built in chat history
  • Feedback Loop
  • Available on - GCP,Azure,AWS.
  • Add RAG with using few lines of Code.
  • Add FAQ generation to chatbot
  • KreateWebsites

  • AI powered websites to domainte search
  • Premium Hosting - Azure, GCP,AWS
  • AI web designer
  • Agent to generate website
  • SEO powered by LLM
  • Content management system for GenAI
  • Buy as Saas Application or managed services
  • Available on Azure Marketplace too.
  • Kreate CMS

  • CMS for GenAI
  • Lineage for GenAI and Human created content
  • Track GenAI and Human Edited content
  • Trace pages that use content
  • Ability to delete GenAI content
  • Generate Slides

  • Give prompt to generate slides
  • Convert slides into webpages
  • Add SEO to slides webpages
  • Content Compass

  • Generate articles
  • Generate images
  • Generate related articles and images
  • Get suggestion what to write next