Find and compare the best Artificial Intelligence software for Tune AI in 2025
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Use the comparison tool below to compare the top Artificial Intelligence software for Tune AI on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Vertex AI
Google
630 RatingsFully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection. -
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Google Cloud Platform
Google
Free ($300 in free credits) 55,297 RatingsGoogle Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging. -
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OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.
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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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GPT-3.5 is the next evolution to GPT 3 large language model, OpenAI. GPT-3.5 models are able to understand and generate natural languages. There are four main models available with different power levels that can be used for different tasks. The main GPT-3.5 models can be used with the text completion endpoint. There are models that can be used with other endpoints. Davinci is the most versatile model family. It can perform all tasks that other models can do, often with less instruction. Davinci is the best choice for applications that require a deep understanding of the content. This includes summarizations for specific audiences and creative content generation. These higher capabilities mean that Davinci is more expensive per API call and takes longer to process than other models.
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Playground AI
Playground AI
$15 per month 2 RatingsPlayground AI is an online AI image creator that is free to use. It can be used to create and edit art, social posts, presentations and logos. -
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OpenRouter
OpenRouter
$2 one-time paymentOpenRouter provides a unified interface to LLMs. OpenRouter scouts for the lowest prices and best latencies/throughputs across dozens of providers, and lets you choose how to prioritize them. You don't need to change code when switching models or providers. You can even allow users to choose and pay for them. Evaluating models is flawed. Instead, compare them by how often they are used for different purposes. Chat with multiple people at once in a chatroom. Users, developers or both can pay for model usage. Model availability may change. APIs are also available to retrieve models, prices and limits. OpenRouter will route requests to the most suitable providers for your model based on your preferences. Requests are by default load-balanced to maximize uptime across the top providers, but you can customize this using the provider object within the request body. Prioritize providers who have not experienced significant outages within the last 10 seconds. -
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Microsoft Fabric
Microsoft
$156.334/month/ 2CU Connecting every data source with analytics services on a single AI-powered platform will transform how people access, manage, and act on data and insights. All your data. All your teams. All your teams in one place. Create an open, lake-centric hub to help data engineers connect data from various sources and curate it. This will eliminate sprawl and create custom views for all. Accelerate analysis through the development of AI models without moving data. This reduces the time needed by data scientists to deliver value. Microsoft Teams, Microsoft Excel, and Microsoft Teams are all great tools to help your team innovate faster. Connect people and data responsibly with an open, scalable solution. This solution gives data stewards more control, thanks to its built-in security, compliance, and governance. -
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Hugging Face
Hugging Face
$9 per monthAutoTrain is a new way to automatically evaluate, deploy and train state-of-the art Machine Learning models. AutoTrain, seamlessly integrated into the Hugging Face ecosystem, is an automated way to develop and deploy state of-the-art Machine Learning model. Your account is protected from all data, including your training data. All data transfers are encrypted. Today's options include text classification, text scoring and entity recognition. Files in CSV, TSV, or JSON can be hosted anywhere. After training is completed, we delete all training data. Hugging Face also has an AI-generated content detection tool. -
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Llama 3
Meta
FreeMeta AI is our intelligent assistant that allows people to create, connect and get things done. We've integrated Llama 3. Meta AI can be used to code and solve problems, allowing you to see the performance of Llama 3. Llama 3, in 8B or 70B, will give you the flexibility and capabilities you need to create your ideas, whether you're creating AI-powered agents or other applications. We've updated our Responsible Use Guide (RUG), to provide the most comprehensive and up-to-date information on responsible development using LLMs. Our system-centric approach includes updates for our trust and security tools, including Llama Guard 2 optimized to support MLCommons' newly announced taxonomy, code shield and Cybersec Evaluation 2. -
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Azure OpenAI Service
Microsoft
$0.0004 per 1000 tokensYou can use advanced language models and coding to solve a variety of problems. To build cutting-edge applications, leverage large-scale, generative AI models that have deep understandings of code and language to allow for new reasoning and comprehension. These coding and language models can be applied to a variety use cases, including writing assistance, code generation, reasoning over data, and code generation. Access enterprise-grade Azure security and detect and mitigate harmful use. Access generative models that have been pretrained with trillions upon trillions of words. You can use them to create new scenarios, including code, reasoning, inferencing and comprehension. A simple REST API allows you to customize generative models with labeled information for your particular scenario. To improve the accuracy of your outputs, fine-tune the hyperparameters of your model. You can use the API's few-shot learning capability for more relevant results and to provide examples. -
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Mixtral 8x7B
Mistral AI
FreeMixtral 8x7B has open weights and is a high quality sparse mixture expert model (SMoE). Licensed under Apache 2.0. Mixtral outperforms Llama 70B in most benchmarks, with 6x faster Inference. It is the strongest model with an open-weight license and the best overall model in terms of cost/performance tradeoffs. It matches or exceeds GPT-3.5 in most standard benchmarks. -
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GPT-4o
OpenAI
$5.00 /1M tokens GPT-4o (o for "omni") is an important step towards a more natural interaction between humans and computers. It accepts any combination as input, including text, audio and image, and can generate any combination of outputs, including text, audio and image. It can respond to audio in as little as 228 milliseconds with an average of 325 milliseconds. This is similar to the human response time in a conversation (opens in new window). It is as fast and cheaper than GPT-4 Turbo on text in English or code. However, it has a significant improvement in text in non-English language. GPT-4o performs better than existing models at audio and vision understanding. -
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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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Mistral Large 2
Mistral AI
FreeMistral Large 2 comes with a 128k window that supports dozens of different languages, including French, German and Spanish. It also supports Arabic, Hindi, Russian and Chinese. It also supports 80+ programming languages, including Python, Java and C++. Mistral Large 2 was designed with single-node applications in mind. Its size of 123 million parameters allows it to run fast on a single computer. Mistral Large 2 is released under the Mistral Research License which allows modification and usage for research and noncommercial purposes. -
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Mixtral 8x22B
Mistral AI
FreeMixtral 8x22B is our latest open model. It sets new standards for performance and efficiency in the AI community. It is a sparse Mixture-of-Experts model (SMoE), which uses only 39B active variables out of 141B. This offers unparalleled cost efficiency in relation to its size. It is fluently bilingual in English, French Italian, German and Spanish. It has strong math and coding skills. It is natively able to call functions; this, along with the constrained-output mode implemented on La Plateforme, enables application development at scale and modernization of tech stacks. Its 64K context window allows for precise information retrieval from large documents. We build models with unmatched cost-efficiency for their respective sizes. This allows us to deliver the best performance-tocost ratio among models provided by the Community. Mixtral 8x22B continues our open model family. Its sparse patterns of activation make it faster than any 70B model. -
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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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Tune Studio
NimbleBox
$10/user/ month Tune Studio is a versatile and intuitive platform that allows users to fine-tune AI models with minimum effort. It allows users to customize machine learning models that have been pre-trained to meet their specific needs, without needing to be a technical expert. Tune Studio's user-friendly interface simplifies the process for uploading datasets and configuring parameters. It also makes it easier to deploy fine-tuned machine learning models. Tune Studio is ideal for beginners and advanced AI users alike, whether you're working with NLP, computer vision or other AI applications. It offers robust tools that optimize performance, reduce the training time and accelerate AI development. -
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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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Amazon Bedrock
Amazon
Amazon Bedrock is a managed AWS service designed to make building and scaling generative AI applications easier by providing access to a diverse range of foundation models (FMs) from leading providers such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can test, fine-tune, and customize these models to meet specific use cases using advanced techniques like Retrieval Augmented Generation (RAG). The platform allows for the creation of intelligent agents that seamlessly integrate with enterprise systems and data sources, enabling enhanced automation and decision-making. Bedrock’s serverless architecture removes the need for infrastructure management, ensuring high scalability and minimal operational complexity. With a focus on security, data privacy, and responsible AI, Amazon Bedrock empowers organizations to accelerate innovation while maintaining trust and compliance. It represents a powerful tool for businesses aiming to integrate cutting-edge AI solutions into their operations effortlessly. -
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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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Mistral 7B
Mistral AI
We solve the most difficult problems to make AI models efficient, helpful and reliable. We are the pioneers of open models. We give them to our users, and empower them to share their ideas. Mistral-7B is a powerful, small model that can be adapted to many different use-cases. Mistral 7B outperforms Llama 13B in all benchmarks. It has 8k sequence length, natural coding capabilities, and is faster than Llama 2. It is released under Apache 2.0 License and we made it simple to deploy on any cloud. -
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GPT-4o mini
OpenAI
A small model with superior textual Intelligence and multimodal reasoning. GPT-4o Mini's low cost and low latency enable a wide range of tasks, including applications that chain or paralelize multiple model calls (e.g. calling multiple APIs), send a large amount of context to the models (e.g. full code base or history of conversations), or interact with clients through real-time, fast text responses (e.g. customer support chatbots). GPT-4o Mini supports text and vision today in the API. In the future, it will support text, image and video inputs and outputs. The model supports up to 16K outputs tokens per request and has knowledge until October 2023. It has a context of 128K tokens. The improved tokenizer shared by GPT-4o makes it easier to handle non-English text. -
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Weights & Biases
Weights & Biases
Weights & Biases allows for experiment tracking, hyperparameter optimization and model and dataset versioning. With just 5 lines of code, you can track, compare, and visualise ML experiments. Add a few lines of code to your script and you'll be able to see live updates to your dashboard each time you train a different version of your model. Our hyperparameter search tool is scalable to a massive scale, allowing you to optimize models. Sweeps plug into your existing infrastructure and are lightweight. Save all the details of your machine learning pipeline, including data preparation, data versions, training and evaluation. It's easier than ever to share project updates. Add experiment logging to your script in a matter of minutes. Our lightweight integration is compatible with any Python script. W&B Weave helps developers build and iterate their AI applications with confidence.
