Choosing the right LLM for your startup in 2024
All-Rounders
If you're seeking a reliable, well-rounded model that can handle a wide range of tasks, these three models are your safest bets.
GPT-4o
GPT-4o, the latest iteration of OpenAI's flagship language model, offers unparalleled performance across various domains while being multi-modal.
Claude 3.5 Sonnet
Claude 3.5 Sonnet from Anthropic is a highly capable model - the only one that can match (or even surpass) GPT-4o in terms of performance - and sports a much larger (200k) context window.
Llama 3.1 405B
Llama 3.1 405B from Meta is the largest openly available foundation model to date, providing unparalleled performance in general knowledge, steerability, math, tool use, and multilingual translation. It’s also an open model meaning that it can be hosted by you on your own cloud providers.
Lowest Cost
For startups operating on a tight budget, these models offer a cost-effective solution without compromising too much on performance.
Llama 3.1 8B
Llama 3.1 model with 8B parameters hosted on Groq is the fastest and most cost effective while offering the best performance out of the smaller models. A multilingual model designed for efficient dialogue applications it excels in tasks involving text and code in multiple languages, including English, French, and Spanish.
Gemini 1.5 Flash
Google's fastest and most cost-efficient multimodal language model, optimized for high-frequency tasks across audio, images, video, and text. With a context window of up to 1 million tokens, it excels in applications like summarization, categorization, and multimodal understanding, making it ideal for developers seeking low-latency solutions
GPT-4o-mini
OpenAI's most cost-efficient small model, designed for fast, lightweight tasks while outperforming previous models in math and coding proficiency. With a context window of 128K tokens and multimodal capabilities, it supports a wide range of applications, making advanced AI accessible and affordable for developers
Fastest Model
When speed, processing power, and response time are of the utmost importance.
Llama 3 8B
Llama 3 8B model, optimised for Groq's tensor streaming processor, is your best bet for speed. This model delivers lightning-fast performance, making it ideal for applications that require real-time or near-real-time responses.
Gemma 7B
A lightweight, open language model from Google, designed for diverse text generation tasks such as question answering and summarization, with 7 billion parameters. It features a context length of 8192 tokens and is optimized for deployment in resource-constrained environments.
Llama 3.1 8B
Llama 3.1 model with 8B parameters hosted on Groq is the fastest and most cost effective while offering the best performance out of the smaller models. A multilingual model designed for efficient dialogue applications it excels in tasks involving text and code in multiple languages, including English, French, and Spanish.
Open Weights Models
For those seeking open solutions, these models offer transparency and flexibility.
Llama 3.1 405B
Meta's largest open-source language model with 405 billion parameters, offering state-of-the-art capabilities in general knowledge, math, and multilingual translation. It features a 128K token context length and built-in tools for web search and code execution, making it a powerhouse for advanced AI applications
Mistral Large 2
A highly efficient and powerful open-source model that rivals closed-source competitors in performance across various benchmarks. It offers exceptional reasoning capabilities and multilingual support, making it a top choice for developers seeking a balance between performance and resource efficiency.
Jamba 1.5 Large
The newest entry in this category, this is an open-source model known for its advanced reasoning abilities and strong performance in specialized tasks like coding and mathematical problem-solving. It stands out for its ability to handle complex, multi-step problems while maintaining a relatively compact size compared to larger models.
RAG Models
RAG (Retrieval Augmented Generation) models excel at tasks that require retrieving and integrating information from external sources. For instance, searching through a database of PDF files and pulling out insights.
Gemini 1.5 Pro
Google's Gemini 1.5 Pro is a stand-out in this category, offering robust performance in information retrieval and generation.
Copy Generation
When you need to generate compelling, human sounding copy.
Claude
Anthropic's Claude models are highly recommended and have demonstrated exceptional proficiency in crafting engaging and persuasive content, making them an ideal choice for marketing and advertising copy.
Long Context Models
When your model demands the ability to process and understand long sequences of text.
Gemini 1.5 Pro
Gemini 1.5 Pro is a mid-size multimodal language model from Google, optimized for complex reasoning tasks across audio, images, video, and text, with a context window of up to 2 million tokens. Its advanced capabilities in understanding and generating content make it a leading choice for developers seeking high-performance AI solutions.
Jamba 1.5 Large
The newest entry in this category, this is an open-source model known for its advanced reasoning abilities and strong performance in specialized tasks like coding and mathematical problem-solving. It stands out for its ability to handle complex, multi-step problems while maintaining a relatively compact size compared to larger models.
Claude 3.5 Sonnet
Claude 3.5 Sonnet from Anthropic is a highly capable model - the only one that can match (or even surpass) GPT-4o in terms of performance - and sports a much larger (200k) context window.
Multimodal Models
Multimodal models capable of processing and generating content across multiple modalities (text, images, audio, etc.) and are becoming increasingly sought-after.
GPT-4
GPT-4, the latest iteration of OpenAI's flagship language model, offers unparalleled performance across various domains while being multi-modal.
Claude Opus
Claude Opus from Anthropic is a highly capable model - the only one that can match GPT-4 in terms of performance - and sports a much larger context window.
Gemini
Need a description
The AI landscape is evolving rapidly, and new models are being released regularly. This information is current as of August 2024, but check for updates regularly to ensure you're leveraging the most suitable model for your needs.
So, like many things when building a startup, the real answer to “which LLM should I use?” is “it depends”. We suggest putting some deep consideration into the problem you want to solve and then working backward to find the generative AI model that will work for you.