Find and compare the best Artificial Intelligence software for Gopher in 2025
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Use the comparison tool below to compare the top Artificial Intelligence software for Gopher on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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ChatGPT is an OpenAI language model. It can generate human-like responses to a variety prompts, and has been trained on a wide range of internet texts. ChatGPT can be used to perform natural language processing tasks such as conversation, question answering, and text generation. ChatGPT is a pretrained language model that uses deep-learning algorithms to generate text. It was trained using large amounts of text data. This allows it to respond to a wide variety of prompts with human-like ease. It has a transformer architecture that has been proven to be efficient in many NLP tasks. ChatGPT can generate text in addition to answering questions, text classification and language translation. This allows developers to create powerful NLP applications that can do specific tasks more accurately. ChatGPT can also process code and generate it.
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GPT-4 (Generative Pretrained Transformer 4) a large-scale, unsupervised language model that is yet to be released. GPT-4, which is the successor of GPT-3, is part of the GPT -n series of natural-language processing models. It was trained using a dataset of 45TB text to produce text generation and understanding abilities that are human-like. GPT-4 is not dependent on additional training data, unlike other NLP models. It can generate text and answer questions using its own context. GPT-4 has been demonstrated to be capable of performing a wide range of tasks without any task-specific training data, such as translation, summarization and sentiment analysis.
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BERT is a large language model that can be used to pre-train language representations. Pre-training refers the process by which BERT is trained on large text sources such as Wikipedia. The training results can then be applied to other Natural Language Processing tasks (NLP), such as sentiment analysis and question answering. You can train many NLP models with AI Platform Training and BERT in just 30 minutes.
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Stable LM
Stability AI
FreeStableLM: Stability AI language models StableLM builds upon our experience with open-sourcing previous language models in collaboration with EleutherAI. This nonprofit research hub. These models include GPTJ, GPTNeoX and the Pythia Suite, which were all trained on The Pile dataset. Cerebras GPT and Dolly-2 are two recent open-source models that continue to build upon these efforts. StableLM was trained on a new dataset that is three times bigger than The Pile and contains 1.5 trillion tokens. We will provide more details about the dataset at a later date. StableLM's richness allows it to perform well in conversational and coding challenges, despite the small size of its dataset (3-7 billion parameters, compared to GPT-3's 175 billion). The development of Stable LM 3B broadens the range of applications that are viable on the edge or on home PCs. This means that individuals and companies can now develop cutting-edge technologies with strong conversational capabilities – like creative writing assistance – while keeping costs low and performance high. -
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Llama 3.2
Meta
FreeThere are now more versions of the open-source AI model that you can refine, distill and deploy anywhere. Choose from 1B or 3B, or build with Llama 3. Llama 3.2 consists of a collection large language models (LLMs), which are pre-trained and fine-tuned. They come in sizes 1B and 3B, which are multilingual text only. Sizes 11B and 90B accept both text and images as inputs and produce text. Our latest release allows you to create highly efficient and performant applications. Use our 1B and 3B models to develop on-device applications, such as a summary of a conversation from your phone, or calling on-device features like calendar. Use our 11B and 90B models to transform an existing image or get more information from a picture of your surroundings. -
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Dolly
Databricks
FreeDolly is an inexpensive LLM that demonstrates a surprising amount of the capabilities of ChatGPT. Whereas the work from the Alpaca team showed that state-of-the-art models could be coaxed into high quality instruction-following behavior, we find that even years-old open source models with much earlier architectures exhibit striking behaviors when fine tuned on a small corpus of instruction training data. Dolly uses an open source model with 6 billion parameters from EleutherAI, which is modified to include new capabilities like brainstorming and text creation that were not present in the original. -
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Llama 3.1
Meta
FreeOpen source AI model that you can fine-tune and distill anywhere. Our latest instruction-tuned models are available in 8B 70B and 405B version. Our open ecosystem allows you to build faster using a variety of product offerings that are differentiated and support your use cases. Choose between real-time or batch inference. Download model weights for further cost-per-token optimization. Adapt to your application, improve using synthetic data, and deploy on-prem. Use Llama components and extend the Llama model using RAG and zero shot tools to build agentic behavior. Use 405B high-quality data to improve specialized model for specific use cases. -
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Llama 3.3
Meta
FreeLlama 3.3, the latest in the Llama language model series, was developed to push the limits of AI-powered communication and understanding. Llama 3.3, with its enhanced contextual reasoning, improved generation of language, and advanced fine tuning capabilities, is designed to deliver highly accurate responses across diverse applications. This version has a larger dataset for training, refined algorithms to improve nuanced understanding, and reduced biases as compared to previous versions. Llama 3.3 excels at tasks such as multilingual communication, technical explanations, creative writing and natural language understanding. It is an indispensable tool for researchers, developers and businesses. Its modular architecture enables customization in specialized domains and ensures performance at scale. -
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Llama 2
Meta
FreeThe next generation of the large language model. This release includes modelweights and starting code to pretrained and fine tuned Llama languages models, ranging from 7B-70B parameters. Llama 1 models have a context length of 2 trillion tokens. Llama 2 models have a context length double that of Llama 1. The fine-tuned Llama 2 models have been trained using over 1,000,000 human annotations. Llama 2, a new open-source language model, outperforms many other open-source language models in external benchmarks. These include tests of reasoning, coding and proficiency, as well as knowledge tests. Llama 2 has been pre-trained using publicly available online data sources. Llama-2 chat, a fine-tuned version of the model, is based on publicly available instruction datasets, and more than 1 million human annotations. We have a wide range of supporters in the world who are committed to our open approach for today's AI. These companies have provided early feedback and have expressed excitement to build with Llama 2 -
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Llama
Meta
Llama (Large Language Model meta AI) is a state of the art foundational large language model that was created to aid researchers in this subfield. Llama allows researchers to use smaller, more efficient models to study these models. This further democratizes access to this rapidly-changing field. Because it takes far less computing power and resources than large language models, such as Llama, to test new approaches, validate other's work, and explore new uses, training smaller foundation models like Llama can be a desirable option. Foundation models are trained on large amounts of unlabeled data. This makes them perfect for fine-tuning for many tasks. We make Llama available in several sizes (7B-13B, 33B and 65B parameters), and also share a Llama card that explains how the model was built in line with our Responsible AI practices.
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