Open source models

Extracted Attributes

• Type

  Development Model

• Purpose

  Promote universal access to product design and modifications; counter proprietary code limitations

• Benefits

  Transparency, flexibility, customization, cost-effectiveness, rapid innovation, democratization of AI, mitigation of vendor lock-in

• Challenges

  Resource-intensive for training and deployment; requires technical expertise

• Comparison

  Contrasted with proprietary models (e.g., Google LaMDA, OpenAI ChatGPT)

• Applications

  E-commerce, appropriate technology, drug discovery, natural language processing (NLP), AI applications (text generation, sentiment analysis, language translation)

• Availability

  Source code freely available for modification and redistribution

• Core Principle

  Peer production

Timeline

• The term 'open source' was coined and the Open Source Initiative (OSI) was founded, marking a period when the open source model gained significant hold with the rise of the Internet. (Source: Historical Context (implied by Wikipedia 'Open source' and general knowledge of OSI founding))

  1998-02-09

• The Chinese company DeepSeek disrupted the AI markets with its R1 large language model, demonstrating how open source LLMs can compete with commercial offerings using more affordable hardware. (Source: Web Search (IBM))

  2025-01-01

Open source

Open source is source code that is made freely available for possible modification and redistribution. Products include permission to use and view the source code, design documents, or content of the product. The open source model is a decentralized software development model that encourages open collaboration. A main principle of open source software development is peer production, with products such as source code, blueprints, and documentation freely available to the public. The open source movement in software began as a response to the limitations of proprietary code. The model is used for projects such as in open source eCommerce, open source appropriate technology, and open source drug discovery. Open source promotes universal access via an open-source or free license to a product's design or blueprint, and universal redistribution of that design or blueprint. Before the phrase open source became widely adopted, developers and producers used a variety of other terms, such as free software, shareware, and public domain software. Open source gained hold with the rise of the Internet. The open-source software movement arose to clarify copyright, licensing, domain, and consumer issues. Generally, open source refers to a computer program in which the source code is available to the general public for usage, modification from its original design, and publication of their version (fork) back to the community. Many large formal institutions have sprung up to support the development of the open-source movement, including the Apache Software Foundation, which supports community projects such as the open-source framework and the open-source HTTP server Apache HTTP.

Web Search Results

• Top 10 open source LLMs for 2025 - Instaclustr

  Open source LLMs are fully accessible for anyone to use, modify, and distribute (although some models require prior approval to use, and some might restrict commercial use of the model). This transparency allows for extensive customization and examination, enabling users to adapt the models to their needs. Open source models offer more freedom, often requiring less financial investment and enabling users to mitigate vendor lock-in risks. [...] Open source large language models have revolutionized natural language processing (NLP) and artificial intelligence (AI) applications by enabling advanced text generation, sentiment analysis, language translation, and more. However, training and deploying these models can be resource-intensive and complex. NetApp Instaclustr steps in to support open source large language models, providing a robust infrastructure and managed services that simplify the process. In this article, we will explore [...] Large Language Models (LLMs) are machine learning models that can understand and generate human language based on large-scale datasets. Unlike proprietary models developed by companies like OpenAI and Google, open source LLMs are licensed to be freely used, modified, and distributed by anyone. They offer transparency and flexibility, which can be particularly useful for research, development, and customization in various applications.

• What Is Open Source Software? - IBM

  As another example, IBM® Granite™AI models, available under Apache 2.0 licenses on Hugging Face and GitHub, deliver comparable performance to larger systems but require far fewer computing resources, showcasing how open source models can provide more efficient alternatives in the generative AI space. Moreover, open source AI provides a cost-effective solution for organizations seeking to fine-tune their generative AI models with proprietary data. [...] Open source LLMs, in particular, are vital to the generative AI ecosystem because they promote a more transparent, accessible and community-driven approach compared to proprietary models. Compared to proprietary LLM models, such as Google’s LaMDA and OpenAI’s ChatGPT-3 and GPT-4 , open source LLMs offer distinct benefits. For instance, they allow developers to inspect, modify and improve the models, enabling rapid innovation and customization. [...] In 2025, the Chinese company DeepSeek disrupted the AI markets with R1, its large language model that costs just USD 5.6 million to train, a fraction compared to commercial leaders such as ChatGPT. This development demonstrated how open source LLMs can compete with commercial offerings, in this case, using more affordable hardware and fewer advanced microchips.5 This shift underscores how open source models contribute to generative AI technology’s democratization.

• Top open source AI models and tools - Inworld AI

  ### Control and integration Control and integration are other essential aspects to evaluate. Open source AI models provide unlimited access to customize models to fit your exact needs and flexibility that's hard to match! On the other hand, commercial solutions are purpose built for specific use cases and often provide better out of the box performance that can reduce the time and effort needed to tweak and adjust models for optimal results. ### Data privacy and compliance [...] Our commitment to developing open source AI models is a testament to our belief that collaboration fuels innovation. Together with the open source community, we’re going to push forward innovations in generative AI that elevate the generative AI and gaming development communities. [...] The technical capabilities of your team are also crucial! Deploying, customizing, and maintaining complex open source AI models requires a certain level of expertise. If your team is equipped with this, then open source AI projects can be a great choice! Otherwise, if you lack these capabilities in-house, an end to end commercial solution might be a better fit. Commercial products often come with robust documentation and technical support which makes it easier for teams to implement and manage.

• steven2358/awesome-generative-ai: A curated list of ... - GitHub

  by Facebook is a suite of decoder-only pre-trained transformers. Announcement. OPT-175B text generation hosted by Alpa. Bloom - BLOOM by Hugging Face is a model similar to GPT-3 that has been trained on 46 different languages and 13 programming languages. #opensource Llama - Meta's open source large language model. #opensource Claude - Talk to Claude, an AI assistant from Anthropic. [...] Repomix - Pack your codebase into AI-friendly formats. #opensource llama.cpp - Inference of Meta's LLaMA model (and others) in pure C/C++. #opensource bitnet.cpp - Official inference framework for 1-bit LLMs, by Microsoft. #opensource OpenRouter - A unified interface for LLMs. #opensource Ludwig - A low-code framework for building custom AI models like LLMs and other deep neural networks. #opensource

• Open-source software development - Wikipedia

  Model ----- [edit] Not to be confused with Open-source model. Image 4 Process-Data Model for open-source software development [...] | Models | | Developmental | Agile EUP Executable UML Incremental model Iterative model Prototype model RAD Scrum "Scrum (software development)") Spiral model UP V-model "V-model (software development)") Waterfall model XP Model-driven engineering Round-trip engineering | | --- | | Other | CMMI Data model ER model Function model Information model Metamodeling Object model SPICE Systems model View model | | Languages | IDEF SysML UML USL | | [...] It is hard to run an open-source project following a more traditional software development method like the waterfall model, because in these traditional methods it is not allowed to go back to a previous phase. In open-source software development, requirements are rarely gathered before the start of the project; instead they are based on early releases of the software product, as Robbins describes.( Besides requirements, often volunteer staff is attracted to help develop the software product