Find and compare the best Artificial Intelligence software for Gemma 2 in 2025
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Use the comparison tool below to compare the top Artificial Intelligence software for Gemma 2 on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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LM-Kit.NET is an enterprise-grade toolkit designed for seamlessly integrating generative AI into your .NET applications, fully supporting Windows, Linux, and macOS. Empower your C# and VB.NET projects with a flexible platform that simplifies the creation and orchestration of dynamic AI agents. Leverage efficient Small Language Models for on‑device inference, reducing computational load, minimizing latency, and enhancing security by processing data locally. Experience the power of Retrieval‑Augmented Generation (RAG) to boost accuracy and relevance, while advanced AI agents simplify complex workflows and accelerate development. Native SDKs ensure smooth integration and high performance across diverse platforms. With robust support for custom AI agent development and multi‑agent orchestration, LM‑Kit.NET streamlines prototyping, deployment, and scalability—enabling you to build smarter, faster, and more secure solutions trusted by professionals worldwide.
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TensorFlow
TensorFlow
Free 2 RatingsOpen source platform for machine learning. TensorFlow is a machine learning platform that is open-source and available to all. It offers a flexible, comprehensive ecosystem of tools, libraries, and community resources that allows researchers to push the boundaries of machine learning. Developers can easily create and deploy ML-powered applications using its tools. Easy ML model training and development using high-level APIs such as Keras. This allows for quick model iteration and debugging. No matter what language you choose, you can easily train and deploy models in cloud, browser, on-prem, or on-device. It is a simple and flexible architecture that allows you to quickly take new ideas from concept to code to state-of the-art models and publication. TensorFlow makes it easy to build, deploy, and test. -
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TorchScript allows you to seamlessly switch between graph and eager modes. TorchServe accelerates the path to production. The torch-distributed backend allows for distributed training and performance optimization in production and research. PyTorch is supported by a rich ecosystem of libraries and tools that supports NLP, computer vision, and other areas. PyTorch is well-supported on major cloud platforms, allowing for frictionless development and easy scaling. Select your preferences, then run the install command. Stable is the most current supported and tested version of PyTorch. This version should be compatible with many users. Preview is available for those who want the latest, but not fully tested, and supported 1.10 builds that are generated every night. Please ensure you have met the prerequisites, such as numpy, depending on which package manager you use. Anaconda is our preferred package manager, as it installs all dependencies.
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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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Fully 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. Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
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Google Colab
Google
7 RatingsGoogle Colab is a cloud-based Jupyter Notebook environment that allows users to write and execute Python code without any setup required. It provides access to powerful computing resources, including GPUs and TPUs, making it an excellent tool for machine learning, data analysis, and academic research. Colab is designed for collaborative work, enabling users to share notebooks with others, track changes, and easily integrate with Google Drive for file storage. It is particularly beneficial for both beginners and professionals seeking a free, interactive platform for experimenting with code and data. With Colab notebooks, you can integrate executable code with rich text, images, LaTeX, HTML, and other elements in a single document. All notebooks you create are saved to your Google Drive. Sharing with colleagues or friends is easy, allowing them to comment or edit your work. Additionally, Colab now provides a Data Science Agent that automates the entire analysis process, from data understanding to delivering insights in a functional notebook. (Note: Sequences are shortened, and results are for illustration. The Data Science Agent may occasionally make errors.) -
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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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Google AI Studio
Google
FreeGoogle AI Studio is an online tool that's free and allows individuals and small groups to create apps and chatbots by using natural language prompting. It allows users to create API keys and prompts for app development. Google AI Studio allows users to discover Gemini Pro's APIs, create prompts and fine-tune Gemini. It also offers generous free quotas, allowing 60 requests a minute. Google has also developed a Generative AI Studio based on Vertex AI. It has models of various types that allow users to generate text, images, or audio content. -
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LlamaCoder
LlamaCoder
FreeOpen source tool that allows you to create small apps by using a single prompt. Powered by Llama 405B and Together.ai. -
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VESSL AI
VESSL AI
$100 + compute/month Fully managed infrastructure, tools and workflows allow you to build, train and deploy models faster. Scale inference and deploy custom AI & LLMs in seconds on any infrastructure. Schedule batch jobs to handle your most demanding tasks, and only pay per second. Optimize costs by utilizing GPUs, spot instances, and automatic failover. YAML simplifies complex infrastructure setups by allowing you to train with a single command. Automate the scaling up of workers during periods of high traffic, and scaling down to zero when inactive. Deploy cutting edge models with persistent endpoints within a serverless environment to optimize resource usage. Monitor system and inference metrics, including worker counts, GPU utilization, throughput, and latency in real-time. Split traffic between multiple models to evaluate. -
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Kaggle
Kaggle
Kaggle provides a Jupyter Notebooks environment that is customizable and easy to set up. You can access free GPUs and a large repository of community-published data & codes. Kaggle contains all the code and data you need for data science. You can conquer any analysis with over 19,000 public datasets, and 200,000 public notebooks. -
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LangChain
LangChain
We believe that the most effective and differentiated applications won't only call out via an API to a language model. LangChain supports several modules. We provide examples, how-to guides and reference docs for each module. Memory is the concept that a chain/agent calls can persist in its state. LangChain provides a standard interface to memory, a collection memory implementations and examples of agents/chains that use it. This module outlines best practices for combining language models with your own text data. Language models can often be more powerful than they are alone. -
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Gemma
Google
Gemma is the family of lightweight open models that are built using the same research and technology as the Gemini models. Gemma was developed by Google DeepMind, along with other teams within Google. The name is derived from the Latin gemma meaning "precious stones". We're also releasing new tools to encourage developer innovation, encourage collaboration, and guide responsible use of Gemma model. Gemma models are based on the same infrastructure and technical components as Gemini, Google's largest and most powerful AI model. Gemma 2B, 7B and other open models can achieve the best performance possible for their size. Gemma models can run directly on a desktop or laptop computer for developers. Gemma is able to surpass much larger models in key benchmarks, while adhering our rigorous standards of safe and responsible outputs. -
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Pipeshift
Pipeshift
Pipeshift is an orchestration platform that allows for the deployment and scaling of open-source AI components. This includes embeddings and vector databases as well as large language models, audio models and vision models. The platform is cloud-agnostic and offers end-toend orchestration to ensure seamless integration and management. Pipeshift's enterprise-grade security is a solution for DevOps, MLOps, and MLOps teams looking to build production pipelines within their own organization, instead of using experimental API providers who may not have privacy concerns. The key features include an enterprise MLOps dashboard for managing AI workloads like fine-tuning and distillation; multi-cloud orchestration, with built-in autoscalers and load balancers; and Kubernetes Cluster Management. -
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NVIDIA DRIVE
NVIDIA
Software is what transforms a vehicle into a smart machine. Open source software stack NVIDIA DRIVE™, enables developers to quickly build and deploy a variety state-of the-art AV applications. This includes perception, localization, mapping, driver monitoring, planning and control, driver monitoring and natural language processing. DRIVE OS, the foundation of the DRIVE SoftwareStack, is the first secure operating system for accelerated computation. It includes NvMedia to process sensor input, NVIDIACUDA®, libraries for parallel computing implementations that are efficient, NVIDIA TensorRT™ for real time AI inference, as well as other tools and modules for accessing hardware engines. NVIDIA DriveWorks®, a SDK that provides middleware functions over DRIVE OS, is essential for autonomous vehicle development. These include the sensor abstraction layer (SAL), sensor plugins, data recorder and vehicle I/O support. -
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nexos.ai
nexos.ai
nexos.ai, a powerful model-gateway, delivers AI solutions that are game-changing. Using intelligent decision-making and advanced automation, nexos.ai simplifies operations, boosts productivity, and accelerates business growth.
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