Page 29 | Top On-Premises Artificial Intelligence Software in 2025

Find and compare the best On-Premises Artificial Intelligence software in 2025

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Use the comparison tool below to compare the top On-Premises Artificial Intelligence software on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

1

Llama

Meta

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Llama (Large Language Model Meta AI) stands as a cutting-edge foundational large language model aimed at helping researchers push the boundaries of their work within this area of artificial intelligence. By providing smaller yet highly effective models like Llama, the research community can benefit even if they lack extensive infrastructure, thus promoting greater accessibility in this dynamic and rapidly evolving domain. Creating smaller foundational models such as Llama is advantageous in the landscape of large language models, as it demands significantly reduced computational power and resources, facilitating the testing of innovative methods, confirming existing research, and investigating new applications. These foundational models leverage extensive unlabeled datasets, making them exceptionally suitable for fine-tuning across a range of tasks. We are offering Llama in multiple sizes (7B, 13B, 33B, and 65B parameters), accompanied by a detailed Llama model card that outlines our development process while adhering to our commitment to Responsible AI principles. By making these resources available, we aim to empower a broader segment of the research community to engage with and contribute to advancements in AI.
2

OPT

Meta

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Large language models, often requiring extensive computational resources for training over long periods, have demonstrated impressive proficiency in zero- and few-shot learning tasks. Due to the high investment needed for their development, replicating these models poses a significant challenge for many researchers. Furthermore, access to the few models available via API is limited, as users cannot obtain the complete model weights, complicating academic exploration. In response to this, we introduce Open Pre-trained Transformers (OPT), a collection of decoder-only pre-trained transformers ranging from 125 million to 175 billion parameters, which we intend to share comprehensively and responsibly with interested scholars. Our findings indicate that OPT-175B exhibits performance on par with GPT-3, yet it is developed with only one-seventh of the carbon emissions required for GPT-3's training. Additionally, we will provide a detailed logbook that outlines the infrastructure hurdles we encountered throughout the project, as well as code to facilitate experimentation with all released models, ensuring that researchers have the tools they need to explore this technology further.
3

T5

Google

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We introduce T5, a model that transforms all natural language processing tasks into a consistent text-to-text format, ensuring that both inputs and outputs are text strings, unlike BERT-style models which are limited to providing either a class label or a segment of the input text. This innovative text-to-text approach enables us to utilize the same model architecture, loss function, and hyperparameter settings across various NLP tasks such as machine translation, document summarization, question answering, and classification, including sentiment analysis. Furthermore, T5's versatility extends to regression tasks, where it can be trained to output the textual form of a number rather than the number itself, showcasing its adaptability. This unified framework greatly simplifies the handling of diverse NLP challenges, promoting efficiency and consistency in model training and application.
4

PanGu-α

Huawei

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PanGu-α has been created using the MindSpore framework and utilizes a powerful setup of 2048 Ascend 910 AI processors for its training. The training process employs an advanced parallelism strategy that leverages MindSpore Auto-parallel, which integrates five different parallelism dimensions—data parallelism, operation-level model parallelism, pipeline model parallelism, optimizer model parallelism, and rematerialization—to effectively distribute tasks across the 2048 processors. To improve the model's generalization, we gathered 1.1TB of high-quality Chinese language data from diverse fields for pretraining. We conduct extensive tests on PanGu-α's generation capabilities across multiple situations, such as text summarization, question answering, and dialogue generation. Additionally, we examine how varying model scales influence few-shot performance across a wide array of Chinese NLP tasks. The results from our experiments highlight the exceptional performance of PanGu-α, demonstrating its strengths in handling numerous tasks even in few-shot or zero-shot contexts, thus showcasing its versatility and robustness. This comprehensive evaluation reinforces the potential applications of PanGu-α in real-world scenarios.
5

Megatron-Turing

NVIDIA

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The Megatron-Turing Natural Language Generation model (MT-NLG) stands out as the largest and most advanced monolithic transformer model for the English language, boasting an impressive 530 billion parameters. This 105-layer transformer architecture significantly enhances the capabilities of previous leading models, particularly in zero-shot, one-shot, and few-shot scenarios. It exhibits exceptional precision across a wide range of natural language processing tasks, including completion prediction, reading comprehension, commonsense reasoning, natural language inference, and word sense disambiguation. To foster further research on this groundbreaking English language model and to allow users to explore and utilize its potential in various language applications, NVIDIA has introduced an Early Access program for its managed API service dedicated to the MT-NLG model. This initiative aims to facilitate experimentation and innovation in the field of natural language processing.
6

Galactica

Meta

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The overwhelming amount of information available poses a significant challenge to advancements in science. With the rapid expansion of scientific literature and data, pinpointing valuable insights within this vast sea of information has become increasingly difficult. Nowadays, people rely on search engines to access scientific knowledge, yet these tools alone cannot effectively categorize and organize this complex information. Galactica is an advanced language model designed to capture, synthesize, and analyze scientific knowledge. It is trained on a diverse array of scientific materials, including research papers, reference texts, knowledge databases, and other relevant resources. In various scientific tasks, Galactica demonstrates superior performance compared to existing models. For instance, on technical knowledge assessments involving LaTeX equations, Galactica achieves a score of 68.2%, significantly higher than the 49.0% of the latest GPT-3 model. Furthermore, Galactica excels in reasoning tasks, outperforming Chinchilla in mathematical MMLU with scores of 41.3% to 35.7%, and surpassing PaLM 540B in MATH with a notable 20.4% compared to 8.8%. This indicates that Galactica not only enhances accessibility to scientific information but also improves our ability to reason through complex scientific queries.
7

PanGu-Σ

Huawei

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Recent breakthroughs in natural language processing, comprehension, and generation have been greatly influenced by the development of large language models. This research presents a system that employs Ascend 910 AI processors and the MindSpore framework to train a language model exceeding one trillion parameters, specifically 1.085 trillion, referred to as PanGu-{\Sigma}. This model enhances the groundwork established by PanGu-{\alpha} by converting the conventional dense Transformer model into a sparse format through a method known as Random Routed Experts (RRE). Utilizing a substantial dataset of 329 billion tokens, the model was effectively trained using a strategy called Expert Computation and Storage Separation (ECSS), which resulted in a remarkable 6.3-fold improvement in training throughput through the use of heterogeneous computing. Through various experiments, it was found that PanGu-{\Sigma} achieves a new benchmark in zero-shot learning across multiple downstream tasks in Chinese NLP, showcasing its potential in advancing the field. This advancement signifies a major leap forward in the capabilities of language models, illustrating the impact of innovative training techniques and architectural modifications.
8

CODENO

Zynk Software

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CODENO is an innovative offering from ZYNK designed to revolutionize the digital transformation of your business. Experience swift enhancements in your operations within just a few weeks by leveraging artificial intelligence and data insights, which unify all your data sources effortlessly. This platform empowers you to boost productivity, refine workflows, and enhance decision-making capabilities for better outcomes. By adopting CODENO, your enterprise can unlock new levels of effectiveness and agility in a competitive landscape.
9

Profet AI

Profet AI

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Profet AI’s No-Code AutoML Platform, which is end-to-end and can be used by manufacturers as their Virtual Data Scientist, provides a complete solution for data analysis. It allows IT/domain experts to quickly build high-quality predictive models and deploy Industrial AI apps to solve their daily production and digitalization challenges. Profet AI AutoML Platform has been widely adopted by leading companies in the world across industries. These include leading EMS, Semi OSAT, PCB design houses, IC design houses, display panel and material solution providers. We use the successful cases of industry leading companies to benefit our customers and implement AI within a week.
10

AmigoChat

AmigoChat

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AmigoChat represents a groundbreaking advancement in AI technology, functioning as a conversational platform that delivers rapid and effective responses. This innovative chatbot not only grants users a higher degree of flexibility but also showcases a variety of conversational skills and a distinctive sense of humor, distinguishing it from other AI companions, such as ChatGPT. The engaging nature of AmigoChat fosters a more enjoyable interaction, making it a preferred choice for those seeking a lively conversational partner.
11

Carmen Axis Video Application

Adaptive Recognition

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The Carmen® Axis Video Application significantly upgrades Axis cameras by integrating sophisticated Automatic Number Plate Recognition (ANPR) and Make and Model Recognition (MMR) features. Users can choose from various deployment methods, including cloud processing through Carmen® Cloud for enhanced scalability and worldwide accessibility, or opt for on-camera processing that guarantees secure and dependable functionality without the need for extra equipment. This application delivers outstanding precision in recognizing license plates across the globe, enabling real-time data collection on vehicles for purposes such as traffic management, security measures, and access control systems. With its ability to seamlessly integrate and offer adaptable licensing arrangements, it serves as a highly effective solution tailored to meet a range of operational requirements. Additionally, the application’s user-friendly interface facilitates ease of use for operators in diverse environments.
12

AutoAlign Sidecar

AutoAlign

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AutoAlign’s Sidecar solutions represent a groundbreaking advancement as the pioneering AI supervisors that engage dynamically with LLMs, enhancing their reliability, compliance, security, and overall effectiveness. As a result, it is now possible to transform every LLM into a more secure, intelligent, and powerful tool. Sidecar stands out as the sole solution with proven capabilities to enhance performance, reliability, security, and safety. By offering the most comprehensive generative AI security, Sidecar enables businesses to utilize safe and effective AI solutions throughout their operations. Consequently, enterprises can now confidently implement generative AI technologies that guarantee positive outcomes, elevate user safety, and maintain strict compliance with industry standards. This innovative approach not only streamlines processes but also fosters a culture of trust and accountability in AI deployment.
13

Chinchilla

Google DeepMind

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Chinchilla is an advanced language model that operates with a compute budget comparable to Gopher while having 70 billion parameters and utilizing four times the amount of data. This model consistently and significantly surpasses Gopher (280 billion parameters), as well as GPT-3 (175 billion), Jurassic-1 (178 billion), and Megatron-Turing NLG (530 billion), across a wide variety of evaluation tasks. Additionally, Chinchilla's design allows it to use significantly less computational power during the fine-tuning and inference processes, which greatly enhances its applicability in real-world scenarios. Notably, Chinchilla achieves a remarkable average accuracy of 67.5% on the MMLU benchmark, marking over a 7% enhancement compared to Gopher, showcasing its superior performance in the field. This impressive capability positions Chinchilla as a leading contender in the realm of language models.
14

NavAI

NavAI

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NavAI.com, a revolutionary AI platform, is designed to empower business with actionable insights and intelligent decision-making abilities. NavAI transforms data into meaningful information by leveraging advanced technologies, such as machine-learning, natural language processing and predictive analytics. Its conversational interface allows users to ask questions using plain language and receive immediate, precise answers. This makes data analysis intuitive and accessible to teams across industries. The platform provides proactive insights, real time updates, and data visualisation tools that simplify complex datasets. NavAI allows businesses to forecast market trends, optimize their operations, and personalize the customer experience with unmatched accuracy. Its robust capabilities include market forecasting, live monitoring, and creating visually appealing charts and reports to aid in strategic planning.