Compare Models
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Microsoft
Azure OpenAI Service
OTHERMicrosoft’s Azure OpenAI Service allows you to take advantage of large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. GPT-4 is available in preview in the Azure OpenAI Service and the billing for GPT-4 8K and 32K instances per 1/K tokens and can be found under those models on the tokes compare site. To note, Microsoft’s Azure OpenAI Service customers can access GPT-3.5, ChatGPT, and DALL·E too. -
Microsoft
Bing Search APIs
OTHERMicrosoft’s Bing AI search engine is powered by GPT-4. Microsoft claims the new model is faster and more accurate than ever. Bing Search APIs provide a variety of APIs with trained models for your use. The Bing Search APIs add intelligent search to your app, combining hundreds of billions of webpages, images, videos, and news to provide relevant results without ads. The results can be automatically customized to your user’s locations or markets, increasing relevancy by staying local. There are various prices for Bing Search APIs which are dependent on the feature. For customers who are interested in more flexible terms related to presenting Bing API results with their models check out the website for prices per 1,000 transactions. -
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. -
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. -
AI21 Labs
Jurassic-2 Grande (Base & Instruct)
$0.01J2-Grande offers enhanced text generation capabilities, making it well-suited to language tasks with a greater degree of complexity. Its fine-tuning options allow for optimization of quality, while maintaining an affordable price and high efficiency (see site for more details). It is an ideal choice for complex language processing tasks and generative text applications. All of J2 models support several non-English languages, including: Spanish, French, German, Portuguese, Italian and Dutch. All Jurassic foundation models are trained on a massive corpus of text, making them a powerful basis for a wide range of natural language processing applications, capable of understanding and composing human-like text. Models are available through an API and you can start with a free trial and then pay based on usage. -
AI21 Labs
Jurassic-2 Jumbo (Base & Instruct)
$0.015As the largest and most powerful model in the Jurassic series, J2-Jumbo is an ideal choice for the most complex language processing tasks and generative text applications. Further, the model can be fine-tuned for optimum performance in any custom application. Jurassic-2 not only improves upon Jurassic-1 (AI21 Studio previous generation models) in every aspect, making it highly versatile in general purpose text-generators, and capable of composing human-like text and solving complex tasks such as question answering and text classification. All of the J2 models support several non-English languages, including: Spanish, French, German, Portuguese, Italian and Dutch. All Jurassic foundation models are trained on a massive corpus of text, making them a powerful basis for a wide range of natural language processing applications, capable of understanding and composing human-like text. Models are available through an API and you can start with a free trial and then pay based on usage. -
AI21 Labs
Jurassic-2 Large (Base & Instruct)
$0.003Designed for fast responses, the Jurassic-2 Large model can be fine-tuned to optimize performance for relatively simple tasks, making it an ideal choice for language processing tasks that require maximum affordability and less processing power. All of the J2 models support several non-English languages, including: Spanish, French, German, Portuguese, Italian and Dutch. All Jurassic foundation models are trained on a massive corpus of text, making them a powerful basis for a wide range of natural language processing applications, capable of understanding and composing human-like text. Models are available through an API and you can start with a free trial and then pay based on usage.
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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. -
StableLM
StableLM-Base-Alpha -7B
FREEStability AI released a new open-source language model, StableLM. The Alpha version of the model is available in 3 billion and 7 billion parameters. StableLM is trained on a new experimental dataset built on The Pile, but three times larger with 1.5 trillion tokens of content. The richness of this dataset gives StableLM surprisingly high performance in conversational and coding tasks, despite its small size. The models are now available on GitHub and on Hugging Face, and developers can freely inspect, use, and adapt our StableLM base models for commercial or research purposes subject to the terms of the CC BY-SA-4.0 license.
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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).
