Alternatives to NVIDIA Nemotron
Compare NVIDIA Nemotron alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to NVIDIA Nemotron in 2025. Compare features, ratings, user reviews, pricing, and more from NVIDIA Nemotron competitors and alternatives in order to make an informed decision for your business.
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1
Llama 3.3
Meta
Llama 3.3 is the latest iteration in the Llama series of language models, developed to push the boundaries of AI-powered understanding and communication. With enhanced contextual reasoning, improved language generation, and advanced fine-tuning capabilities, Llama 3.3 is designed to deliver highly accurate, human-like responses across diverse applications. This version features a larger training dataset, refined algorithms for nuanced comprehension, and reduced biases compared to its predecessors. Llama 3.3 excels in tasks such as natural language understanding, creative writing, technical explanation, and multilingual communication, making it an indispensable tool for businesses, developers, and researchers. Its modular architecture allows for customizable deployment in specialized domains, ensuring versatility and performance at scale.Starting Price: Free -
2
Smaug-72B
Abacus
Smaug-72B is a powerful open-source large language model (LLM) known for several key features: High Performance: It currently holds the top spot on the Hugging Face Open LLM leaderboard, surpassing models like GPT-3.5 in various benchmarks. This means it excels at tasks like understanding, responding to, and generating human-like text. Open Source: Unlike many other advanced LLMs, Smaug-72B is freely available for anyone to use and modify, fostering collaboration and innovation in the AI community. Focus on Reasoning and Math: It specifically shines in handling reasoning and mathematical tasks, attributing this strength to unique fine-tuning techniques developed by Abacus AI, the creators of Smaug-72B. Based on Qwen-72B: It's technically a fine-tuned version of another powerful LLM called Qwen-72B, released by Alibaba, further improving upon its capabilities. Overall, Smaug-72B represents a significant step forward in open-source AI.Starting Price: Free -
3
Baichuan-13B
Baichuan Intelligent Technology
Baichuan-13B is an open source and commercially available large-scale language model containing 13 billion parameters developed by Baichuan Intelligent following Baichuan -7B . It has achieved the best results of the same size on authoritative Chinese and English benchmarks. This release contains two versions of pre-training ( Baichuan-13B-Base ) and alignment ( Baichuan-13B-Chat ). Larger size, more data : Baichuan-13B further expands the number of parameters to 13 billion on the basis of Baichuan -7B , and trains 1.4 trillion tokens on high-quality corpus, which is 40% more than LLaMA-13B. It is currently open source The model with the largest amount of training data in the 13B size. Support Chinese and English bilingual, use ALiBi position code, context window length is 4096.Starting Price: Free -
4
IBM Granite
IBM
IBM® Granite™ is a family of artificial intelligence (AI) models purpose-built for business, engineered from scratch to help ensure trust and scalability in AI-driven applications. Open source Granite models are available today. We make AI as accessible as possible for as many developers as possible. That’s why we have open-sourced core Granite Code, Time Series, Language, and GeoSpatial models and made them available on Hugging Face under permissive Apache 2.0 license that enables broad, unencumbered commercial usage. All Granite models are trained on carefully curated data, with industry-leading levels of transparency about the data that went into them. We have also open-sourced the tools we use to ensure the data is high quality and up to the standards that enterprise-grade applications demand.Starting Price: Free -
5
OpenGPT-X
OpenGPT-X
OpenGPT-X is a German initiative focused on developing large AI language models tailored to European needs, emphasizing versatility, trustworthiness, multilingual capabilities, and open-source accessibility. The project brings together a consortium of partners to cover the entire generative AI value chain, from scalable, GPU-based infrastructure and data for training large language models to model design and practical applications through prototypes and proofs of concept. OpenGPT-X aims to advance cutting-edge research with a strong focus on business applications, thereby accelerating the adoption of generative AI in the German economy. The project also emphasizes responsible AI development, ensuring that the models are trustworthy and align with European values and regulations. The project provides resources such as the LLM Workbook, and a three-part reference guide with resources and examples to help users understand the key features of large AI language models.Starting Price: Free -
6
Qwen
Alibaba
Qwen LLM refers to a family of large language models (LLMs) developed by Alibaba Cloud's Damo Academy. These models are trained on a massive dataset of text and code, allowing them to understand and generate human-like text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Here are some key features of Qwen LLMs: Variety of sizes: The Qwen series ranges from 1.8 billion to 72 billion parameters, offering options for different needs and performance levels. Open source: Some versions of Qwen are open-source, which means their code is publicly available for anyone to use and modify. Multilingual support: Qwen can understand and translate multiple languages, including English, Chinese, and French. Diverse capabilities: Besides generation and translation, Qwen models can be used for tasks like question answering, text summarization, and code generation.Starting Price: Free -
7
Tülu 3
Ai2
Tülu 3 is an advanced instruction-following language model developed by the Allen Institute for AI (Ai2), designed to enhance capabilities in areas such as knowledge, reasoning, mathematics, coding, and safety. Built upon the Llama 3 Base, Tülu 3 employs a comprehensive four-stage post-training process: meticulous prompt curation and synthesis, supervised fine-tuning on a diverse set of prompts and completions, preference tuning using both off- and on-policy data, and a novel reinforcement learning approach to bolster specific skills with verifiable rewards. This open-source model distinguishes itself by providing full transparency, including access to training data, code, and evaluation tools, thereby closing the performance gap between open and proprietary fine-tuning methods. Evaluations indicate that Tülu 3 outperforms other open-weight models of similar size, such as Llama 3.1-Instruct and Qwen2.5-Instruct, across various benchmarks.Starting Price: Free -
8
GPT4All
Nomic AI
GPT4All is an ecosystem to train and deploy powerful and customized large language models that run locally on consumer-grade CPUs. The goal is simple - be the best instruction-tuned assistant-style language model that any person or enterprise can freely use, distribute and build on. A GPT4All model is a 3GB - 8GB file that you can download and plug into the GPT4All open-source ecosystem software. Nomic AI supports and maintains this software ecosystem to enforce quality and security alongside spearheading the effort to allow any person or enterprise to easily train and deploy their own on-edge large language models. Data is one the most important ingredients to successfully building a powerful, general-purpose large language model. The GPT4All community has built the GPT4All open source data lake as a staging ground for contributing instruction and assistant tuning data for future GPT4All model trains.Starting Price: Free -
9
OpenEuroLLM
OpenEuroLLM
OpenEuroLLM is a collaborative initiative among Europe's leading AI companies and research institutions to develop a series of open-source foundation models for transparent AI in Europe. The project emphasizes transparency by openly sharing data, documentation, training, testing code, and evaluation metrics, fostering community involvement. It ensures compliance with EU regulations, aiming to provide performant large language models that align with European standards. A key focus is on linguistic and cultural diversity, extending multilingual capabilities to encompass all EU official languages and beyond. The initiative seeks to enhance access to foundational models ready for fine-tuning across various applications, expand evaluation results in multiple languages, and increase the availability of training datasets and benchmarks. Transparency is maintained throughout the training processes by sharing tools, methodologies, and intermediate results. -
10
PygmalionAI
PygmalionAI
PygmalionAI is a community dedicated to creating open-source projects based on EleutherAI's GPT-J 6B and Meta's LLaMA models. In simple terms, Pygmalion makes AI fine-tuned for chatting and roleplaying purposes. The current actively supported Pygmalion AI model is the 7B variant, based on Meta AI's LLaMA model. With only 18GB (or less) VRAM required, Pygmalion offers better chat capability than much larger language models with relatively minimal resources. Our curated dataset of high-quality roleplaying data ensures that your bot will be the optimal RP partner. Both the model weights and the code used to train it are completely open-source, and you can modify/re-distribute it for whatever purpose you want. Language models, including Pygmalion, generally run on GPUs since they need access to fast memory and massive processing power in order to output coherent text at an acceptable speed.Starting Price: Free -
11
GPT-5
OpenAI
GPT-5 is the anticipated next iteration of OpenAI's Generative Pre-trained Transformer, a large language model (LLM) still under development. LLMs are trained on massive amounts of text data and are able to generate realistic and coherent text, translate languages, write different kinds of creative content, and answer your questions in an informative way. It's not publicly available yet. OpenAI hasn't announced a release date, but some speculate it could be launched sometime in 2024. It's expected to be even more powerful than its predecessor, GPT-4. GPT-4 is already impressive, capable of generating human-quality text, translating languages, and writing different kinds of creative content. GPT-5 is expected to take these abilities even further, with better reasoning, factual accuracy, and ability to follow instructions.Starting Price: $0.0200 per 1000 tokens -
12
Grok 3
xAI
Grok-3, developed by xAI, represents a significant advancement in the field of artificial intelligence, aiming to set new benchmarks in AI capabilities. It is designed to be a multimodal AI, capable of processing and understanding data from various sources including text, images, and audio, which allows for a more integrated and comprehensive interaction with users. Grok-3 is built on an unprecedented scale, with training involving ten times more computational resources than its predecessor, leveraging 100,000 Nvidia H100 GPUs on the Colossus supercomputer. This extensive computational power is expected to enhance Grok-3's performance in areas like reasoning, coding, and real-time analysis of current events through direct access to X posts. The model is anticipated to outperform not only its earlier versions but also compete with other leading AI models in the generative AI landscape.Starting Price: Free -
13
Open R1
Open R1
Open R1 is a community-driven, open-source initiative aimed at replicating the advanced AI capabilities of DeepSeek-R1 through transparent methodologies. You can try Open R1 AI model or DeepSeek R1 free online chat on Open R1. The project offers a comprehensive implementation of DeepSeek-R1's reasoning-optimized training pipeline, including tools for GRPO training, SFT fine-tuning, and synthetic data generation, all under the MIT license. While the original training data remains proprietary, Open R1 provides the complete toolchain for users to develop and fine-tune their own models.Starting Price: Free -
14
Cerebras-GPT
Cerebras
State-of-the-art language models are extremely challenging to train; they require huge compute budgets, complex distributed compute techniques and deep ML expertise. As a result, few organizations train large language models (LLMs) from scratch. And increasingly those that have the resources and expertise are not open sourcing the results, marking a significant change from even a few months back. At Cerebras, we believe in fostering open access to the most advanced models. With this in mind, we are proud to announce the release to the open source community of Cerebras-GPT, a family of seven GPT models ranging from 111 million to 13 billion parameters. Trained using the Chinchilla formula, these models provide the highest accuracy for a given compute budget. Cerebras-GPT has faster training times, lower training costs, and consumes less energy than any publicly available model to date.Starting Price: Free -
15
R1 1776
Perplexity AI
Perplexity AI has open-sourced R1 1776, a large language model (LLM) based on DeepSeek R1 designed to enhance transparency and foster community collaboration in AI development. This release allows researchers and developers to access the model's architecture and codebase, enabling them to contribute to its improvement and adaptation for various applications. By sharing R1 1776 openly, Perplexity AI aims to promote innovation and ethical practices within the AI community.Starting Price: Free -
16
OLMo 2
Ai2
OLMo 2 is a family of fully open language models developed by the Allen Institute for AI (AI2), designed to provide researchers and developers with transparent access to training data, open-source code, reproducible training recipes, and comprehensive evaluations. These models are trained on up to 5 trillion tokens and are competitive with leading open-weight models like Llama 3.1 on English academic benchmarks. OLMo 2 emphasizes training stability, implementing techniques to prevent loss spikes during long training runs, and utilizes staged training interventions during late pretraining to address capability deficiencies. The models incorporate state-of-the-art post-training methodologies from AI2's Tülu 3, resulting in the creation of OLMo 2-Instruct models. An actionable evaluation framework, the Open Language Modeling Evaluation System (OLMES), was established to guide improvements through development stages, consisting of 20 evaluation benchmarks assessing core capabilities. -
17
Qwen-7B
Alibaba
Qwen-7B is the 7B-parameter version of the large language model series, Qwen (abbr. Tongyi Qianwen), proposed by Alibaba Cloud. Qwen-7B is a Transformer-based large language model, which is pretrained on a large volume of data, including web texts, books, codes, etc. Additionally, based on the pretrained Qwen-7B, we release Qwen-7B-Chat, a large-model-based AI assistant, which is trained with alignment techniques. The features of the Qwen-7B series include: Trained with high-quality pretraining data. We have pretrained Qwen-7B on a self-constructed large-scale high-quality dataset of over 2.2 trillion tokens. The dataset includes plain texts and codes, and it covers a wide range of domains, including general domain data and professional domain data. Strong performance. In comparison with the models of the similar model size, we outperform the competitors on a series of benchmark datasets, which evaluates natural language understanding, mathematics, coding, etc. And more.Starting Price: Free -
18
Cohere
Cohere AI
Cohere is an enterprise AI platform that enables developers and businesses to build powerful language-based applications. Specializing in large language models (LLMs), Cohere provides solutions for text generation, summarization, and semantic search. Their model offerings include the Command family for high-performance language tasks and Aya Expanse for multilingual applications across 23 languages. Focused on security and customization, Cohere allows flexible deployment across major cloud providers, private cloud environments, or on-premises setups to meet diverse enterprise needs. The company collaborates with industry leaders like Oracle and Salesforce to integrate generative AI into business applications, improving automation and customer engagement. Additionally, Cohere For AI, their research lab, advances machine learning through open-source projects and a global research community.Starting Price: Free -
19
ChatGPT
OpenAI
ChatGPT is a language model developed by OpenAI. It has been trained on a diverse range of internet text, allowing it to generate human-like responses to a variety of prompts. ChatGPT can be used for various natural language processing tasks, such as question answering, conversation, and text generation. ChatGPT is a pre-trained language model that uses deep learning algorithms to generate text. It was trained on a large corpus of text data, allowing it to generate human-like responses to a wide range of prompts. The model has a transformer architecture, which has been shown to be effective in many NLP tasks. In addition to generating text, ChatGPT can also be fine-tuned for specific NLP tasks such as question answering, text classification, and language translation. This allows developers to build powerful NLP applications that can perform specific tasks more accurately. ChatGPT can also process and generate code.Starting Price: Free -
20
Llama 2
Meta
The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters. Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations. Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests. Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations. We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.Starting Price: Free -
21
Yi-Large
01.AI
Yi-Large is a proprietary large language model developed by 01.AI, offering a 32k context length with both input and output costs at $2 per million tokens. It stands out with its advanced capabilities in natural language processing, common-sense reasoning, and multilingual support, performing on par with leading models like GPT-4 and Claude3 in various benchmarks. Yi-Large is designed for tasks requiring complex inference, prediction, and language understanding, making it suitable for applications like knowledge search, data classification, and creating human-like chatbots. Its architecture is based on a decoder-only transformer with enhancements such as pre-normalization and Group Query Attention, and it has been trained on a vast, high-quality multilingual dataset. This model's versatility and cost-efficiency make it a strong contender in the AI market, particularly for enterprises aiming to deploy AI solutions globally.Starting Price: $0.19 per 1M input token -
22
NVIDIA NeMo
NVIDIA
NVIDIA NeMo LLM is a service that provides a fast path to customizing and using large language models trained on several frameworks. Developers can deploy enterprise AI applications using NeMo LLM on private and public clouds. They can also experience Megatron 530B—one of the largest language models—through the cloud API or experiment via the LLM service. Customize your choice of various NVIDIA or community-developed models that work best for your AI applications. Within minutes to hours, get better responses by providing context for specific use cases using prompt learning techniques. Leverage the power of NVIDIA Megatron 530B, one of the largest language models, through the NeMo LLM Service or the cloud API. Take advantage of models for drug discovery, including in the cloud API and NVIDIA BioNeMo framework. -
23
Phi-4
Microsoft
Phi-4 is a 14B parameter state-of-the-art small language model (SLM) that excels at complex reasoning in areas such as math, in addition to conventional language processing. Phi-4 is the latest member of our Phi family of small language models and demonstrates what’s possible as we continue to probe the boundaries of SLMs. Phi-4 is currently available on Azure AI Foundry under a Microsoft Research License Agreement (MSRLA) and will be available on Hugging Face. Phi-4 outperforms comparable and larger models on math related reasoning due to advancements throughout the processes, including the use of high-quality synthetic datasets, curation of high-quality organic data, and post-training innovations. Phi-4 continues to push the frontier of size vs quality. -
24
OpenELM
Apple
OpenELM is an open-source language model family developed by Apple. It uses a layer-wise scaling strategy to efficiently allocate parameters within each layer of the transformer model, leading to enhanced accuracy compared to existing open language models of similar size. OpenELM is trained on publicly available datasets and achieves state-of-the-art performance for its size. -
25
Hermes 3
Nous Research
Experiment, and push the boundaries of individual alignment, artificial consciousness, open-source software, and decentralization, in ways that monolithic companies and governments are too afraid to try. Hermes 3 contains advanced long-term context retention and multi-turn conversation capability, complex roleplaying and internal monologue abilities, and enhanced agentic function-calling. Our training data aggressively encourages the model to follow the system and instruction prompts exactly and in an adaptive manner. Hermes 3 was created by fine-tuning Llama 3.1 8B, 70B, and 405B, and training on a dataset of primarily synthetically generated responses. The model boasts comparable and superior performance to Llama 3.1 while unlocking deeper capabilities in reasoning and creativity. Hermes 3 is a series of instruct and tool-use models with strong reasoning and creative abilities.Starting Price: Free -
26
Aya
Cohere AI
Aya is a new state-of-the-art, open-source, massively multilingual, generative large language research model (LLM) covering 101 different languages — more than double the number of languages covered by existing open-source models. Aya helps researchers unlock the powerful potential of LLMs for dozens of languages and cultures largely ignored by most advanced models on the market today. We are open-sourcing both the Aya model, as well as the largest multilingual instruction fine-tuned dataset to-date with a size of 513 million covering 114 languages. This data collection includes rare annotations from native and fluent speakers all around the world, ensuring that AI technology can effectively serve a broad global audience that have had limited access to-date. -
27
RedPajama
RedPajama
Foundation models such as GPT-4 have driven rapid improvement in AI. However, the most powerful models are closed commercial models or only partially open. RedPajama is a project to create a set of leading, fully open-source models. Today, we are excited to announce the completion of the first step of this project: the reproduction of the LLaMA training dataset of over 1.2 trillion tokens. The most capable foundation models today are closed behind commercial APIs, which limits research, customization, and their use with sensitive data. Fully open-source models hold the promise of removing these limitations, if the open community can close the quality gap between open and closed models. Recently, there has been much progress along this front. In many ways, AI is having its Linux moment. Stable Diffusion showed that open-source can not only rival the quality of commercial offerings like DALL-E but can also lead to incredible creativity from broad participation by communities.Starting Price: Free -
28
OPT
Meta
Large language models, which are often trained for hundreds of thousands of compute days, have shown remarkable capabilities for zero- and few-shot learning. Given their computational cost, these models are difficult to replicate without significant capital. For the few that are available through APIs, no access is granted to the full model weights, making them difficult to study. We present Open Pre-trained Transformers (OPT), a suite of decoder-only pre-trained transformers ranging from 125M to 175B parameters, which we aim to fully and responsibly share with interested researchers. We show that OPT-175B is comparable to GPT-3, while requiring only 1/7th the carbon footprint to develop. We are also releasing our logbook detailing the infrastructure challenges we faced, along with code for experimenting with all of the released models. -
29
Janus-Pro-7B
DeepSeek
Janus-Pro-7B is an innovative open-source multimodal AI model from DeepSeek, designed to excel in both understanding and generating content across text, images, and videos. It leverages a unique autoregressive architecture with separate pathways for visual encoding, enabling high performance in tasks ranging from text-to-image generation to complex visual comprehension. This model outperforms competitors like DALL-E 3 and Stable Diffusion in various benchmarks, offering scalability with versions from 1 billion to 7 billion parameters. Licensed under the MIT License, Janus-Pro-7B is freely available for both academic and commercial use, providing a significant leap in AI capabilities while being accessible on major operating systems like Linux, MacOS, and Windows through Docker.Starting Price: Free -
30
Llama 3.2
Meta
The open-source AI model you can fine-tune, distill and deploy anywhere is now available in more versions. Choose from 1B, 3B, 11B or 90B, or continue building with Llama 3.1. Llama 3.2 is a collection of large language models (LLMs) pretrained and fine-tuned in 1B and 3B sizes that are multilingual text only, and 11B and 90B sizes that take both text and image inputs and output text. Develop highly performative and efficient applications from our latest release. Use our 1B or 3B models for on device applications such as summarizing a discussion from your phone or calling on-device tools like calendar. Use our 11B or 90B models for image use cases such as transforming an existing image into something new or getting more information from an image of your surroundings.Starting Price: Free -
31
Sarvam AI
Sarvam AI
We are developing efficient large language models for India's diverse linguistic culture and enabling new GenAI applications through bespoke enterprise models. We are building an enterprise-grade platform that lets you develop and evaluate your company’s GenAI apps. We believe in the power of open-source to accelerate AI innovation and will be contributing to open-source models and datasets, as well be leading efforts for large-scale data curation in public-good space. We are a dynamic and close-knit team of AI pioneers, blending expertise in research, engineering, product design, and business operations. Our diverse backgrounds unite under a shared commitment to excellence in science and the creation of societal impact. We foster an environment where tackling complex tech challenges is not just a job, but a passion. -
32
Gemma 2
Google
A family of state-of-the-art, light-open models created from the same research and technology that were used to create Gemini models. These models incorporate comprehensive security measures and help ensure responsible and reliable AI solutions through selected data sets and rigorous adjustments. Gemma models achieve exceptional comparative results in their 2B, 7B, 9B, and 27B sizes, even outperforming some larger open models. With Keras 3.0, enjoy seamless compatibility with JAX, TensorFlow, and PyTorch, allowing you to effortlessly choose and change frameworks based on task. Redesigned to deliver outstanding performance and unmatched efficiency, Gemma 2 is optimized for incredibly fast inference on various hardware. The Gemma family of models offers different models that are optimized for specific use cases and adapt to your needs. Gemma models are large text-to-text lightweight language models with a decoder, trained in a huge set of text data, code, and mathematical content. -
33
GPT-4
OpenAI
GPT-4 (Generative Pre-trained Transformer 4) is a large-scale unsupervised language model, yet to be released by OpenAI. GPT-4 is the successor to GPT-3 and part of the GPT-n series of natural language processing models, and was trained on a dataset of 45TB of text to produce human-like text generation and understanding capabilities. Unlike most other NLP models, GPT-4 does not require additional training data for specific tasks. Instead, it can generate text or answer questions using only its own internally generated context as input. GPT-4 has been shown to be able to perform a wide variety of tasks without any task specific training data such as translation, summarization, question answering, sentiment analysis and more.Starting Price: $0.0200 per 1000 tokens -
34
Arcee-SuperNova
Arcee.ai
Our new flagship model is a small Language Model (SLM) with all the power and performance of leading closed-source LLMs. Excels at generalized tasks, instruction-following, and human preferences. The best 70B model on the market. SuperNova can be utilized for any generalized task, much like Open AI’s GPT4o, Claude Sonnet 3.5, and Cohere. Trained with the most advanced learning & optimization techniques, SuperNova generates highly accurate responses in human-like text. It's the most flexible, secure, and cost-effective language model on the market, saving customers up to 95% on total deployment costs vs. traditional closed-source models. Use SuperNova to integrate AI into apps and products, for general chat purposes, and for diverse use cases. Regularly update your models with the latest open-source tech, ensuring you're never locked into any one solution. Protect your data with industry-leading privacy measures.Starting Price: Free -
35
Falcon 3
Technology Innovation Institute (TII)
Falcon 3 is an open-source large language model (LLM) developed by the Technology Innovation Institute (TII) to make advanced AI accessible to a broader audience. Designed for efficiency, it operates seamlessly on lightweight devices, including laptops, without compromising performance. The Falcon 3 ecosystem comprises four scalable models, each tailored to diverse applications, and supports multiple languages while optimizing resource usage. This latest iteration in TII's LLM series achieves state-of-the-art results in reasoning, language understanding, instruction following, code, and mathematics tasks. By combining high performance with resource efficiency, Falcon 3 aims to democratize access to AI, empowering users across various sectors to leverage advanced technology without the need for extensive computational resources.Starting Price: Free -
36
PanGu-α
Huawei
PanGu-α is developed under the MindSpore and trained on a cluster of 2048 Ascend 910 AI processors. The training parallelism strategy is implemented based on MindSpore Auto-parallel, which composes five parallelism dimensions to scale the training task to 2048 processors efficiently, including data parallelism, op-level model parallelism, pipeline model parallelism, optimizer model parallelism and rematerialization. To enhance the generalization ability of PanGu-α, we collect 1.1TB high-quality Chinese data from a wide range of domains to pretrain the model. We empirically test the generation ability of PanGu-α in various scenarios including text summarization, question answering, dialogue generation, etc. Moreover, we investigate the effect of model scales on the few-shot performances across a broad range of Chinese NLP tasks. The experimental results demonstrate the superior capabilities of PanGu-α in performing various tasks under few-shot or zero-shot settings. -
37
Granite Code
IBM
We introduce the Granite series of decoder-only code models for code generative tasks (e.g., fixing bugs, explaining code, documenting code), trained with code written in 116 programming languages. A comprehensive evaluation of the Granite Code model family on diverse tasks demonstrates that our models consistently reach state-of-the-art performance among available open source code LLMs. The key advantages of Granite Code models include: All-rounder Code LLM: Granite Code models achieve competitive or state-of-the-art performance on different kinds of code-related tasks, including code generation, explanation, fixing, editing, translation, and more. Demonstrating their ability to solve diverse coding tasks. Trustworthy Enterprise-Grade LLM: All our models are trained on license-permissible data collected following IBM's AI Ethics principles and guided by IBM’s Corporate Legal team for trustworthy enterprise usage.Starting Price: Free -
38
EXAONE
LG
EXAONE is a large language model developed by LG AI Research with the goal of nurturing "Expert AI" in multiple domains. The Expert AI Alliance was formed as a collaborative effort among leading companies in various fields to advance the capabilities of EXAONE. Partner companies within the alliance will serve as mentors, providing skills, knowledge, and data to help EXAONE gain expertise in relevant domains. EXAONE, described as being akin to a college student who has completed general elective courses, requires additional intensive training to become an expert in specific areas. LG AI Research has already demonstrated EXAONE's abilities through real-world applications, such as Tilda, an AI human artist that debuted at New York Fashion Week, as well as AI applications for summarizing customer service conversations and extracting information from complex academic papers. -
39
NLP Cloud
NLP Cloud
Fast and accurate AI models suited for production. Highly-available inference API leveraging the most advanced NVIDIA GPUs. We selected the best open-source natural language processing (NLP) models from the community and deployed them for you. Fine-tune your own models - including GPT-J - or upload your in-house custom models, and deploy them easily to production. Upload or Train/Fine-Tune your own AI models - including GPT-J - from your dashboard, and use them straight away in production without worrying about deployment considerations like RAM usage, high-availability, scalability... You can upload and deploy as many models as you want to production.Starting Price: $29 per month -
40
NVIDIA NeMo Megatron
NVIDIA
NVIDIA NeMo Megatron is an end-to-end framework for training and deploying LLMs with billions and trillions of parameters. NVIDIA NeMo Megatron, part of the NVIDIA AI platform, offers an easy, efficient, and cost-effective containerized framework to build and deploy LLMs. Designed for enterprise application development, it builds upon the most advanced technologies from NVIDIA research and provides an end-to-end workflow for automated distributed data processing, training large-scale customized GPT-3, T5, and multilingual T5 (mT5) models, and deploying models for inference at scale. Harnessing the power of LLMs is made easy through validated and converged recipes with predefined configurations for training and inference. Customizing models is simplified by the hyperparameter tool, which automatically searches for the best hyperparameter configurations and performance for training and inference on any given distributed GPU cluster configuration. -
41
Stable LM
Stability AI
Stable LM: Stability AI Language Models. The release of Stable LM builds on our experience in open-sourcing earlier language models with EleutherAI, a nonprofit research hub. These language models include GPT-J, GPT-NeoX, and the Pythia suite, which were trained on The Pile open-source dataset. Many recent open-source language models continue to build on these efforts, including Cerebras-GPT and Dolly-2. Stable LM is trained on a new experimental dataset built on The Pile, but three times larger with 1.5 trillion tokens of content. We will release details on the dataset in due course. The richness of this dataset gives Stable LM surprisingly high performance in conversational and coding tasks, despite its small size of 3 to 7 billion parameters (by comparison, GPT-3 has 175 billion parameters). Stable LM 3B is a compact language model designed to operate on portable digital devices like handhelds and laptops, and we’re excited about its capabilities and portability.Starting Price: Free -
42
Falcon Mamba 7B
Technology Innovation Institute (TII)
Falcon Mamba 7B is the first open-source State Space Language Model (SSLM), introducing a groundbreaking architecture for Falcon models. Recognized as the top-performing open-source SSLM worldwide by Hugging Face, it sets a new benchmark in AI efficiency. Unlike traditional transformers, SSLMs operate with minimal memory requirements and can generate extended text sequences without additional overhead. Falcon Mamba 7B surpasses leading transformer-based models, including Meta’s Llama 3.1 8B and Mistral’s 7B, showcasing superior performance. This innovation underscores Abu Dhabi’s commitment to advancing AI research and development on a global scale.Starting Price: Free -
43
PanGu-Σ
Huawei
Significant advancements in the field of natural language processing, understanding, and generation have been achieved through the expansion of large language models. This study introduces a system which utilizes Ascend 910 AI processors and the MindSpore framework to train a language model with over a trillion parameters, specifically 1.085T, named PanGu-{\Sigma}. This model, which builds upon the foundation laid by PanGu-{\alpha}, takes the traditionally dense Transformer model and transforms it into a sparse one using a concept known as Random Routed Experts (RRE). The model was efficiently trained on a dataset of 329 billion tokens using a technique called Expert Computation and Storage Separation (ECSS), leading to a 6.3-fold increase in training throughput via heterogeneous computing. Experimentation indicates that PanGu-{\Sigma} sets a new standard in zero-shot learning for various downstream Chinese NLP tasks. -
44
InstructGPT
OpenAI
InstructGPT is an open-source framework for training language models to generate natural language instructions from visual input. It uses a generative pre-trained transformer (GPT) model and the state-of-the-art object detector, Mask R-CNN, to detect objects in images and generate natural language sentences that describe the image. InstructGPT is designed to be effective across domains such as robotics, gaming and education; it can assist robots in navigating complex tasks with natural language instructions, or help students learn by providing descriptive explanations of processes or events.Starting Price: $0.0200 per 1000 tokens -
45
Sky-T1
NovaSky
Sky-T1-32B-Preview is an open source reasoning model developed by the NovaSky team at UC Berkeley's Sky Computing Lab. It matches the performance of proprietary models like o1-preview on reasoning and coding benchmarks, yet was trained for under $450, showcasing the feasibility of cost-effective, high-level reasoning capabilities. The model was fine-tuned from Qwen2.5-32B-Instruct using a curated dataset of 17,000 examples across diverse domains, including math and coding. The training was completed in 19 hours on eight H100 GPUs with DeepSpeed Zero-3 offloading. All aspects of the project, including data, code, and model weights, are fully open-source, empowering the academic and open-source communities to replicate and enhance the model's performance.Starting Price: Free -
46
Palmyra LLM
Writer
Palmyra is a suite of Large Language Models (LLMs) engineered for precise, dependable performance in enterprise applications. These models excel in tasks such as question-answering, image analysis, and support for over 30 languages, with fine-tuning available for industries like healthcare and finance. Notably, Palmyra models have achieved top rankings in benchmarks like Stanford HELM and PubMedQA, and Palmyra-Fin is the first model to pass the CFA Level III exam. Writer ensures data privacy by not using client data to train or modify their models, adopting a zero data retention policy. The Palmyra family includes specialized models such as Palmyra X 004, featuring tool-calling capabilities; Palmyra Med, tailored for healthcare; Palmyra Fin, designed for finance; and Palmyra Vision, which offers advanced image and video processing. These models are available through Writer's full-stack generative AI platform, which integrates graph-based Retrieval Augmented Generation (RAG).Starting Price: $18 per month -
47
Qwen2.5-1M
Alibaba
Qwen2.5-1M is an open-source language model developed by the Qwen team, designed to handle context lengths of up to one million tokens. This release includes two model variants, Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M, marking the first time Qwen models have been upgraded to support such extensive context lengths. To facilitate efficient deployment, the team has also open-sourced an inference framework based on vLLM, integrated with sparse attention methods, enabling processing of 1M-token inputs with a 3x to 7x speed improvement. Comprehensive technical details, including design insights and ablation experiments, are available in the accompanying technical report.Starting Price: Free -
48
VideoPoet
Google
VideoPoet is a simple modeling method that can convert any autoregressive language model or large language model (LLM) into a high-quality video generator. It contains a few simple components. An autoregressive language model learns across video, image, audio, and text modalities to autoregressively predict the next video or audio token in the sequence. A mixture of multimodal generative learning objectives are introduced into the LLM training framework, including text-to-video, text-to-image, image-to-video, video frame continuation, video inpainting and outpainting, video stylization, and video-to-audio. Furthermore, such tasks can be composed together for additional zero-shot capabilities. This simple recipe shows that language models can synthesize and edit videos with a high degree of temporal consistency. -
49
CodeQwen
Alibaba
CodeQwen is the code version of Qwen, the large language model series developed by the Qwen team, Alibaba Cloud. It is a transformer-based decoder-only language model pre-trained on a large amount of data of codes. Strong code generation capabilities and competitive performance across a series of benchmarks. Supporting long context understanding and generation with the context length of 64K tokens. CodeQwen supports 92 coding languages and provides excellent performance in text-to-SQL, bug fixes, etc. You can just write several lines of code with transformers to chat with CodeQwen. Essentially, we build the tokenizer and the model from pre-trained methods, and we use the generate method to perform chatting with the help of the chat template provided by the tokenizer. We apply the ChatML template for chat models following our previous practice. The model completes the code snippets according to the given prompts, without any additional formatting.Starting Price: Free -
50
Falcon-40B
Technology Innovation Institute (TII)
Falcon-40B is a 40B parameters causal decoder-only model built by TII and trained on 1,000B tokens of RefinedWeb enhanced with curated corpora. It is made available under the Apache 2.0 license. Why use Falcon-40B? It is the best open-source model currently available. Falcon-40B outperforms LLaMA, StableLM, RedPajama, MPT, etc. See the OpenLLM Leaderboard. It features an architecture optimized for inference, with FlashAttention and multiquery. It is made available under a permissive Apache 2.0 license allowing for commercial use, without any royalties or restrictions. ⚠️ This is a raw, pretrained model, which should be further finetuned for most usecases. If you are looking for a version better suited to taking generic instructions in a chat format, we recommend taking a look at Falcon-40B-Instruct.Starting Price: Free