Find and compare the best Artificial Intelligence software for Anyscale in 2025
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Use the comparison tool below to compare the top Artificial Intelligence software for Anyscale on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Google Cloud Platform
Google
Free ($300 in free credits) 25 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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Ray
Anyscale
FreeYou can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution. -
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Unify AI
Unify AI
$1 per creditLearn how to choose the right LLM based on your needs, and how you can optimize quality, speed and cost-efficiency. With a single API and standard API, you can access all LLMs from all providers. Set your own constraints for output speed, latency and cost. Define your own quality metric. Personalize your router for your requirements. Send your queries to the fastest providers based on the latest benchmark data for the region you are in, updated every 10 minutes. Unify's dedicated walkthrough will help you get started. Discover the features that you already have and our upcoming roadmap. Create a Unify Account to access all models supported by all providers using a single API Key. Our router balances output speed, quality, and cost according to user preferences. The quality of the output is predicted using a neural scoring system, which predicts each model's ability to respond to a given prompt. -
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MindMac
MindMac
$29 one-time paymentMindMac is a native macOS app that enhances productivity by seamlessly integrating with ChatGPT, and other AI models. It supports multiple AI vendors, including OpenAI and Azure OpenAI. It also supports local LLMs using LMStudio and LocalAI. MindMac comes with over 150 prompt templates that facilitate user interaction. It also allows extensive customization of OpenAI parameters and appearance, context mode, and keyboard shortcuts. The application has a powerful inline feature that allows users to ask questions or generate content within any application, without switching windows. MindMac protects your privacy by storing API key securely in the Mac Keychain. Data is sent directly to the AI provider, without the need for intermediary servers. The app is free with basic features and requires no account to setup. -
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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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Nurix
Nurix
Nurix AI, a Bengaluru based company, specializes in the development and customization of AI agents to automate and enhance enterprise processes across various sectors including sales and customer service. Nurix AI's platform seamlessly integrates with existing enterprise systems. AI agents can execute complex tasks autonomously and provide real-time answers, as well as make intelligent decisions, without constant human supervision. Their proprietary voice-tovoice model is a standout feature, as it supports low-latency human-like conversations, in multiple languages. This enhances customer interactions. Nurix AI provides tailored AI services to startups. It offers end-to-end solutions for building and scaling AI products without extensive in-house teams. Their expertise includes large language models, cloud-integration, inference and model training. This ensures that clients receive enterprise-ready AI products.
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