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. -
ChatGLM
ChatGLM-6B
FREEResearchers at the Tsinghua University in China have worked on developing the ChatGLM series of models that have comparable performance to other models such as GPT-3 and BLOOM. ChatGLM-6B is an open bilingual language model (trained on Chinese and English). It is based on General Language Model (GLM) framework, with 6.2B parameters. With the quantization technique, users can deploy locally on consumer-grade graphics cards (only 6GB of GPU memory is required at the INT4 quantization level). The following models are available: ChatGLM-130B (an open source LLM), ChatGLM-100B (not open source but available through invite-only access), and ChatGLM-6 (a lightweight open source alternative). ChatGLM LLMs are available with a Apache-2.0 license that allows commercial use. We have included the link to the Hugging Face page where you can try the ChatGLM-6B Chatbot for free. -
Deepmind
Chinchilla AI
OTHERGoogle’s DeepMind Chinchilla AI is still in the testing phase. Once released, Chinchilla AI will be useful for developing various artificial intelligence tools, such as chatbots, virtual assistants, and predictive models. It functions in a manner analogous to that of other large language models such as GPT-3 (175B parameters), Jurassic-1 (178B parameters), Gopher (280B parameters), and Megatron-Turing NLG (300B parameters) but because Chinchilla is smaller (70B parameters), inference and fine-tuning costs less, easing the use of these models for smaller companies or universities that may not have the budget or hardware to run larger models.
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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. -
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 -
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). -
LMSYS Org
Vicuna-13B
FREEVicuna-13B is an open-source chatbot developed by a team of researchers from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego. The chatbot was trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT. There is a 13B and 7B parameter models that are available on Hugging Face.
Vicuna-13B achieves more than 90% quality of OpenAI ChatGPT and Google Bard while outperforming other models like LLaMA and Stanford Alpaca in more than 90% of cases. The code and weights and an online demo are publicly available for non-commercial use. Here is a link to learn more about how it compares to other models – https://lmsys.org/blog/2023-03-30-vicuna/.
To use this model, you need to install LLaMA weights first and convert them into Hugging Face weights, and the cost of training Vicuna-13B is around $300.
