Compare Models
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OpenAI
Davinci (fine tuning) GPT-3
$0.12When fine-tuning a GPT model like Davinci, you are fine-tuning the GPT-3 base model (not the instruction-oriented variant of GPT-3). Fine-tuning involves taking the pre-trained base model and further training it on your specific dataset or task to enhance its performance. Fine-tuning allows OpenAI API customers to leverage the power of pre-trained GPT-3 language models, such as Davinci, while tailoring them to their specific needs (the fine-tuning process allows a model to specialize in a specific task or context, making it more efficient and effective for a particular use case, which can help to reduce costs and latency for high-volume tasks). You are also able to continue fine-tuning a fine-tuned model to add additional data without having to start from scratch.Davinci is the largest and most powerful variant of GPT-3. It’s the best choice for tasks requiring the most sophisticated language capabilities, but it also requires more processing power and time to generate results. Note: There are two fine-tuning costs to be aware of, a one-time training cost and a pay-as-you-go usage cost. -
OpenAI
Davinci Instruct model
$0.02Davinci is the most capable Instruct model and it can do any task the other models can (Ada, Babbage and Curie), often with higher quality. InstructGPT models are sibling models to the ChatGPT. They are built on GPT-3 models but made to be safer, more helpful, and more aligned to users’ needs using a technique called reinforcement learning from human feedback (RLHF). Instruct models are meant to generate text with a clear instruction, and they are not optimized for conversational chat. Instruct models are optimized to follow single-turn instructions (e.g., specifically designed to follow instructions provided in a prompt). Developers can use Instruct models for extracting knowledge, generating text, performing NLP tasks, automating tasks involving natural language, and translating languages. Instruct models make up facts less often than GPT-3 base models and show slight decreases in toxic output generation. Access is available through a request to OpenAI’s API. -
OpenAI
GPT-3.5-turbo 16k
$0.004GPT-3.5-turbo 16k has the same capabilities as the standard gpt-3.5-turbo (4k model) but with 4 times the context but at twice the price. In general, a larger context window can be more powerful because it takes into account more information from the surrounding text, which can lead to better predictionsGPT-3.5-turbo was designed to provide better performance and is well-known as the model that, by default, powers ChatGPT. However, paying customers who subscribe to ChatGPT Plus can change the model to GPT-4 before you start a chat.GPT-3.5-turbo is optimized for conversational formats and is superior to GPT-3 models, and the performance of GPT-3.5-turbo is on par with Instruct Davinci-003. GPT-3.5-turbo was trained on a massive corpus of text data, including books, articles, and web pages from across the internet and is used for tasks like content and code generation, question answering, translation, and more. Access is available through a request to OpenAI’s API or through the web application (try for free). -
OpenAI
GPT-3.5-turbo 4k
$0.002GPT-3.5-turbo is an upgraded version of the GPT-3 model. It was designed to provide better performance and is well-known as the model that, by default, powers ChatGPT (however, paying customer who subscribe to ChatGPT Plus can change the model to GPT-4 before you start a chat).GPT-3.5-turbo is optimized for conversational formats and is superior to GPT-3 models, and the performance of GPT-3.5-turbo is on par with Instruct Davinci-003 (however is also ten times cheaper and has been seen to be three times faster). GPT-3.5-turbo was trained on a massive corpus of text data, including books, articles, and web pages from across the internet and is used for tasks like content and code generation, question answering, translation, and more. In some cases, GPT-3.5-turbo results can sometimes be too “chatty” or “creative”. Access is available through a request to OpenAI’s API or through the web application (try for free). -
OpenAI
GPT-4 32K context
$0.12GPT-4 is OpenAI’s new design that incorporates additional improvements and advancements, including being multimodal so it can take both text and image inputs. With broad general knowledge and domain expertise, GPT-4 can follow complex instructions in natural language and solve difficult problems with accuracy. GPT-4 has a more diverse range of training data, incorporating additional languages and sources beyond just English. This means that the model will be able to process and generate text in multiple languages and better understand the nuances and subtleties of different languages and dialects. This is the extended 32k token context-length model, which is separate to the 8k model (and is more expensive).
GPT-4 API access is now available.
Note: At the time of writing, ChatGPT Plus subscribers can access Chat GPT-4 by logging into the web application.
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OpenAI
GPT-4 8K context
$0.06GPT-4 is OpenAI’s new design that incorporates additional improvements and advancements, including being multimodal so it can take both text and image inputs. With broad general knowledge and domain expertise, GPT-4 can follow complex instructions in natural language and solve difficult problems with accuracy. GPT-4 has a more diverse range of training data, incorporating additional languages and sources beyond just English. This means that the model will be able to process and generate text in multiple languages and better understand the nuances and subtleties of different languages and dialects. There are a few different GPT-4 models to choose from. The standard GPT-4 model offers 8k tokens for the context. GPT-4 API access is now available.
Note: For the ChatGPT web application, ChatGPT is powered by GPT-3.5 turbo by default. However, if you are a paying customer and subscribe to ChatGPT Plus, you can change the model to GPT-4 before you start a chat.
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Microsoft, NVIDIA
MT-NLG
OTHERMT-NLG (Megatron-Turing Natural Language Generation) uses the architecture of the transformer-based Megatron to generate coherent and contextually relevant text for a range of tasks, including completion prediction, reading comprehension, commonsense reasoning, natural language inferences, and word sense disambiguation. MT-NLG is the successor to Microsoft Turing NLG 17B and NVIDIA Megatron-LM 8.3B. The MT-NLG model is three times larger than GPT-3 (530B vs 175B). Following the original Megatron work, NVIDIA and Microsoft trained the model on over 4,000 GPUs. NVIDIA has announced an Early Access program for its managed API service to the MT-NLG model for organizations and researchers. -
RedPajama
RedPajama-INCITE-7B-Instruct
FREEThe RedPajama project aims to create a set of leading open source models. RedPajama-INCITE-7B-Instruct was developed by Together and leaders from the open source AI community. RedPajama-INCITE-7B-Instruct model represents the top-performing open source entry on the HELM benchmarks, surpassing other cutting-edge open models like LLaMA-7B, Falcon-7B, and MPT-7B. The instruct-tuned model is designed for versatility and shines when tasked with few-shot performance.The Instruct, Chat, Base Model, and ten interim checkpoints are now available on HuggingFace, and all the RedPajama LLMs come with commercial licenses under Apache 2.0.Play with the RedPajama chat model version here – https://lnkd.in/g3npSEbg -
Amazon
SageMaker
FREEAmazon SageMaker enables developers to create, train, and deploy machine-learning (ML) models in the cloud. SageMaker also enables developers to deploy ML models on embedded systems and edge-devices. Amazon SageMaker JumpStart helps you quickly and easily get started with machine learning. The solutions are fully customizable and supports one-click deployment and fine-tuning of more than 150 popular open source models such as natural language processing, object detection, and image classification models that can help with extracting and analyzing data, fraud detection, churn prediction and personalized recommendations.The Hugging Face LLM Inference DLCs on Amazon SageMaker, allows support the following models: BLOOM / BLOOMZ, MT0-XXL, Galactica, SantaCoder, GPT-Neox 20B (joi, pythia, lotus, rosey, chip, RedPajama, open assistant, FLAN-T5-XXL (T5-11B), Llama (vicuna, alpaca, koala), Starcoder / SantaCoder, and Falcon 7B / Falcon 40B. Hugging Face’s LLM DLC is a new purpose-built Inference Container to easily deploy LLMs in a secure and managed environment. -
OpenAI
text-davinci-003
$0.02Text-davinci-003 is recognized as GPT 3.5 and is a variant of the GPT-3 model. While both Davinci and text-davinci-003 are powerful models, they differ in a few key ways. Text-davinci-003 is a newer and more capable model explicitly designed for instruction-following tasks. Text-davinci-003 was trained on a more recent dataset containing data up to June 2021. It can do any language task with better quality, longer output, and consistent instruction-following than the Curie, Babbage, or Ada models. Text-davinci-003 supports a longer context window (max prompt plus completion length) than Davinci.For those requesting the OpenAI’s API, GPT-3.5-turbo may be a better choice for tasks that require high accuracy in math or zero-shot classification and sentiment analysis than text-davinci-003. To note, GPT-3.5-turbo performs at a similar capability to text-davinci-003 but at 10 percent the price per token. OpenAI recommends GPT-3.5-turbo for most use cases. -
OpenAI
text-embedding-ada-002
$0.0001An embedding API model, such as Ada, is a powerful tool that converts words into numerical representations, enabling computers to understand and process natural language more effectively. This process is crucial for developing machine learning algorithms and artificial intelligence systems that can interact with humans, analyze text, or make predictions based on text. OpenAI’s text embeddings is built for advanced search, clustering, topic modeling, and classification functionality.Access is available through a request to OpenAI’s API. -
Microsoft
VALL-E
OTHERVALL-E is a LLM for text to speech synthesis (TTS) developed by Microsoft (technically it is a neural codec language model). Its creators state that VALL-E could be used for high-quality text-to-speech applications, speech editing where a recording of a person could be edited and changed from a text transcript (making them say something they originally didn’t), and audio content creation when combined with other generative AI models. Studies indicate that VALL-E notably surpasses the leading zero-shot TTS system regarding speech authenticity and resemblance to the speaker. Furthermore, it has been observed that VALL-E is capable of retaining the emotional expression and ambient acoustics of the speaker within the synthesized output. Unfortunately, VALL-E is not available for any form of public consumption at this time. At the time of writing, VALL-E is a research project, and there is no customer onboarding queue or waitlist (but you can apply to be part of the first testers group).
