Compare Models
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OpenAI
Curie Instruct model
$0.002Open AI’s Instruct model Curie is very capable and is faster and costs less than Davinci. Curie can understand and generate natural language. InstructGPT models are sibling models to 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 model also 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.
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OpenAI
DALL·E 2
$0.016DALL-E 2 is a browser-based AI system that can create realistic images and art from a description in natural language. It currently supports the ability, given a prompt, to create a new image with a certain size, edit an existing image, or create variations of a user-provided image. Currently, DALL·E 2 charges for an image by pixel resolution.Also to note, for developers, there is also an API available for the beta version and the API allows you to integrate state of the art image generation capabilities directly into your product. The API usage is offered on a pay-as-you-go basis and is billed separately. To note, OpenAI offers large volume discounts (>$5k/month) through their sale team. -
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. -
Databricks
Dolly 2.0
FREEDolly 2.0 by Databricks, is the first open source, instruction-following Large Language Model, fine-tuned on a human-generated instruction dataset and is licensed for research and commercial use, which means any organization can create, own, and customize powerful LLMs that can talk to people without paying for API access or sharing data with third parties.Dolly 2.0 is a 12B parameter language model based on the EleutherAI pythia model family and fine-tuned exclusively on a new, high-quality human generated instruction following dataset (crowdsourced among Databricks employees – so cool). Dolly-v2-12b is not a state-of-the-art model, but it does exhibit surprisingly high-quality instruction following behavior not characteristic of the foundation model on which it is based. Dolly v2 is also available in smaller model sizes: dolly-v2-7b, a 6.9 billion parameter based on pythia-6.9b and dolly-v2-3b, a 2.8 billion parameter based on pythia-2.8b.Dolly 2.0 can be used for brainstorming, classification, open Q&A, closed Q&A, content generation, information extraction, and summarization. You can access the Dolly 2.0 can training code, the dataset, and the model weights on Hugging Face. -
Google, Stanford University
Electra
FREEELECTRA (Efficiently Learning an Encoder that Classifies Token Replacements Accurately) is a transformer-based model like BERT, but it uses a different pre-training approach, which is more efficient and requires less computational resources. It was created by a team of researchers from Google Research, Brain Team, and Stanford University. ELECTRA models are trained to distinguish “real” input tokens vs “fake” input tokens generated by another neural network (for the more technical audience, ELECTRA uses a new pre-training task, called replaced token detection (RTD), that trains a bidirectional model while learning from all input positions). Inspired by generative adversarial networks (GANs), ELECTRA trains the model to distinguish between “real” and “fake” input data. At small scale, ELECTRA achieves strong results even when trained on a single GPU. At large scale, ELECTRA achieves state-of-the-art results on the SQuAD 2.0 dataset. Go to GitHub where you can access the three models (ELECTRA-Small, ELECTRA-Base and ELECTRA-Large). -
Technology Innovation Institute
Falcon-40B
OTHERThe Technology Innovation Institute (TII), an Abu Dhabi government funded research institution, has introduced Falcon, a state-of-the-art autoregressive decoder-only language model series released under the Apache 2.0 license, which means it can be used for commerical and research uses.
The family includes Falcon-40B and Falcon-7B, trained on 1 trillion tokens, mainly (>80%) from the RefinedWeb datase. A special variant, Falcon-40B-Instruct, has been made available which may be more suitable for assistant-style tasks. Falcon-40B can support English, German, Spanish, French (and limited capabilities in Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish). It can be used to generate creative text and solve complex problems, chatbots, virtual assistants, language translation, content generation, and sentiment analysis (and more).To use these models, PyTorch 2.0 is required. TII is now calling for proposals from users worldwide to submit their most creative ideas for Falcon 40B’s deployment – https://falconllm.tii.ae/call-for-proposal.php or you can pay to access it via Amazon SageMaker JumpStart.
A demo of Falcon-Chat is available on Hugging Face at https://huggingface.co/spaces/HuggingFaceH4/falcon-chat. -
Technology Innovation Institute
Falcon-7B
FREEThe Technology Innovation Institute (TII), an Abu Dhabi government funded research institution, has introduced Falcon, a state-of-the-art autoregressive decoder-only language model series released under the Apache 2.0 license, which means it can be used for commerical and research uses. Falcon-7B only needs ~15GB and therefore is accessible even on consumer hardware. The model can support English, German, Spanish, French (and limited capabilities in Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish). It can be used to generate creative text and solve complex problems, chatbots, customer service operations, virtual assistants, language translation, content generation, and sentiment analysis.
This raw pretrained model should be finetuned for specific use cases. Falcon-7B-Instruct is also available at https://huggingface.co/tiiuae/falcon-7b-instruct.
If you are looking for a version better-suited model to take generic instructions in a chat format, we recommend Falcon-7B-Instruct rather than the base model. -
Google
FLAN-T5
FREEIf you already know T5, FLAN-T5 is just better at everything. For the same number of parameters, these models have been fine-tuned on more than 1,000 additional tasks covering more languages – the NLP is for English, German, French. It has Apache-2.0 license which is a permissive open source license that allows for commercial use. With appropriate prompting, it can perform zero-shot NLP tasks such as text summarization, common sense reasoning, natural language inference, question answering, sentence and sentiment classification, translation, and pronoun resolution. -
Google
Flan-UL2
FREEDeveloped by Google, Flan-UL2, which is a more powerful version of the T5 model that has been trained using Flan, and it is downloadable from Hugging Face. It shows performance exceeding the ‘prior’ versions of Flan-T5. With the ability to reason for itself and generalize better than the previous models, Flan-UL2 is a great improvement. Flan-UL2 is a machine learning model that can generate textual descriptions of images and has the potential to be used for image search, video captioning, automated content generation, and visual question answering. Flan-UL2 has an Apache-2.0 license, which is a permissive open source license that allows for commercial use.If Flan-UL2’s 20B parameters are too much, consider the previous iteration of Flan-T5, which comes in five different sizes and might be more suitable for your needs. -
Cohere
Generate
$0.015Cohere is a Canadian startup that provides high-performance and secure LLMs for the enterprise. Their models work on public, private, or hybrid clouds.Cohere Generate can be used for tasks such as copywriting, named entity recognition, paraphrasing, and summarization. It can be particularly useful for automating time-consuming and repetitive copywriting tasks and re-wording text to suit a specific reader or context.Cohere Generate is available as an API that can be integrated into various libraries using Python, Node, or Go software development kits (SDKs).We have shown the price of the Cohere Generate Default version, but a Cohere Generate Custom model is available but is double the price (0.030 per 1/k tokens). However, custom models can lead to some of the best-performing NLP models for many tasks. -
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).
