Alternatives to NVIDIA NeMo
Compare NVIDIA NeMo alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to NVIDIA NeMo in 2025. Compare features, ratings, user reviews, pricing, and more from NVIDIA NeMo competitors and alternatives in order to make an informed decision for your business.
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1
Vertex AI
Google
Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection. Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex.Starting Price: Free to start -
2
NVIDIA NIM
NVIDIA
Explore the latest optimized AI models, connect AI agents to data with NVIDIA NeMo, and deploy anywhere with NVIDIA NIM microservices. NVIDIA NIM is a set of easy-to-use inference microservices that facilitate the deployment of foundation models across any cloud or data center, ensuring data security and streamlined AI integration. Additionally, NVIDIA AI provides access to the Deep Learning Institute (DLI), offering technical training to gain in-demand skills, hands-on experience, and expert knowledge in AI, data science, and accelerated computing. AI models generate responses and outputs based on complex algorithms and machine learning techniques, and those responses or outputs may be inaccurate, harmful, biased, or indecent. By testing this model, you assume the risk of any harm caused by any response or output of the model. Please do not upload any confidential information or personal data unless expressly permitted. Your use is logged for security purposes. -
3
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. -
4
Megatron-Turing
NVIDIA
Megatron-Turing Natural Language Generation model (MT-NLG), is the largest and the most powerful monolithic transformer English language model with 530 billion parameters. This 105-layer, transformer-based MT-NLG improves upon the prior state-of-the-art models in zero-, one-, and few-shot settings. It demonstrates unmatched accuracy in a broad set of natural language tasks such as, Completion prediction, Reading comprehension, Commonsense reasoning, Natural language inferences, Word sense disambiguation, etc. With the intent of accelerating research on the largest English language model till date and enabling customers to experiment, employ and apply such a large language model on downstream language tasks - NVIDIA is pleased to announce an Early Access program for its managed API service to MT-NLG mode. -
5
GPT-NeoX
EleutherAI
An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library. This repository records EleutherAI's library for training large-scale language models on GPUs. Our current framework is based on NVIDIA's Megatron Language Model and has been augmented with techniques from DeepSpeed as well as some novel optimizations. We aim to make this repo a centralized and accessible place to gather techniques for training large-scale autoregressive language models, and accelerate research into large-scale training.Starting Price: Free -
6
Mistral NeMo
Mistral AI
Mistral NeMo, our new best small model. A state-of-the-art 12B model with 128k context length, and released under the Apache 2.0 license. Mistral NeMo is a 12B model built in collaboration with NVIDIA. Mistral NeMo offers a large context window of up to 128k tokens. Its reasoning, world knowledge, and coding accuracy are state-of-the-art in its size category. As it relies on standard architecture, Mistral NeMo is easy to use and a drop-in replacement in any system using Mistral 7B. We have released pre-trained base and instruction-tuned checkpoints under the Apache 2.0 license to promote adoption for researchers and enterprises. Mistral NeMo was trained with quantization awareness, enabling FP8 inference without any performance loss. The model is designed for global, multilingual applications. It is trained on function calling and has a large context window. Compared to Mistral 7B, it is much better at following precise instructions, reasoning, and handling multi-turn conversations.Starting Price: Free -
7
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 -
8
NVIDIA Nemotron
NVIDIA
NVIDIA Nemotron is a family of open-source models developed by NVIDIA, designed to generate synthetic data for training large language models (LLMs) for commercial applications. The Nemotron-4 340B model, in particular, is a significant release by NVIDIA, offering developers a powerful tool to generate high-quality data and filter it based on various attributes using a reward model. -
9
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. -
10
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 -
11
Mistral Large
Mistral AI
Mistral Large is Mistral AI's flagship language model, designed for advanced text generation and complex multilingual reasoning tasks, including text comprehension, transformation, and code generation. It supports English, French, Spanish, German, and Italian, offering a nuanced understanding of grammar and cultural contexts. With a 32,000-token context window, it can accurately recall information from extensive documents. The model's precise instruction-following and native function-calling capabilities facilitate application development and tech stack modernization. Mistral Large is accessible through Mistral's platform, Azure AI Studio, and Azure Machine Learning, and can be self-deployed for sensitive use cases. Benchmark evaluations indicate that Mistral Large achieves strong results, making it the world's second-ranked model generally available through an API, next to GPT-4.Starting Price: Free -
12
Mistral Small
Mistral AI
On September 17, 2024, Mistral AI announced several key updates to enhance the accessibility and performance of their AI offerings. They introduced a free tier on "La Plateforme," their serverless platform for tuning and deploying Mistral models as API endpoints, enabling developers to experiment and prototype at no cost. Additionally, Mistral AI reduced prices across their entire model lineup, with significant cuts such as a 50% reduction for Mistral Nemo and an 80% decrease for Mistral Small and Codestral, making advanced AI more cost-effective for users. The company also unveiled Mistral Small v24.09, a 22-billion-parameter model offering a balance between performance and efficiency, suitable for tasks like translation, summarization, and sentiment analysis. Furthermore, they made Pixtral 12B, a vision-capable model with image understanding capabilities, freely available on "Le Chat," allowing users to analyze and caption images without compromising text-based performance.Starting Price: Free -
13
Gemini Flash
Google
Gemini Flash is an advanced large language model (LLM) from Google, specifically designed for high-speed, low-latency language processing tasks. Part of Google DeepMind’s Gemini series, Gemini Flash is tailored to provide real-time responses and handle large-scale applications, making it ideal for interactive AI-driven experiences such as customer support, virtual assistants, and live chat solutions. Despite its speed, Gemini Flash doesn’t compromise on quality; it’s built on sophisticated neural architectures that ensure responses remain contextually relevant, coherent, and precise. Google has incorporated rigorous ethical frameworks and responsible AI practices into Gemini Flash, equipping it with guardrails to manage and mitigate biased outputs, ensuring it aligns with Google’s standards for safe and inclusive AI. With Gemini Flash, Google empowers businesses and developers to deploy responsive, intelligent language tools that can meet the demands of fast-paced environments. -
14
Phi-3
Microsoft
A family of powerful, small language models (SLMs) with groundbreaking performance at low cost and low latency. Maximize AI capabilities, lower resource use, and ensure cost-effective generative AI deployments across your applications. Accelerate response times in real-time interactions, autonomous systems, apps requiring low latency, and other critical scenarios. Run Phi-3 in the cloud, at the edge, or on device, resulting in greater deployment and operation flexibility. Phi-3 models were developed in accordance with Microsoft AI principles: accountability, transparency, fairness, reliability and safety, privacy and security, and inclusiveness. Operate effectively in offline environments where data privacy is paramount or connectivity is limited. Generate more coherent, accurate, and contextually relevant outputs with an expanded context window. Deploy at the edge to deliver faster responses. -
15
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. -
16
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. -
17
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 -
18
BioNeMo
NVIDIA
BioNeMo is an AI-powered drug discovery cloud service and framework built on NVIDIA NeMo Megatron for training and deploying large biomolecular transformer AI models at a supercomputing scale. The service includes pre-trained large language models (LLMs) and native support for common file formats for proteins, DNA, RNA, and chemistry, providing data loaders for SMILES for molecular structures and FASTA for amino acid and nucleotide sequences. The BioNeMo framework will also be available for download for running on your own infrastructure. ESM-1, based on Meta AI’s state-of-the-art ESM-1b, and ProtT5 are transformer-based protein language models that can be used to generate learned embeddings for tasks like protein structure and property prediction. OpenFold, a deep learning model for 3D structure prediction of novel protein sequences, will be available in BioNeMo service. -
19
StarCoder
BigCode
StarCoder and StarCoderBase are Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks. Similar to LLaMA, we trained a ~15B parameter model for 1 trillion tokens. We fine-tuned StarCoderBase model for 35B Python tokens, resulting in a new model that we call StarCoder. We found that StarCoderBase outperforms existing open Code LLMs on popular programming benchmarks and matches or surpasses closed models such as code-cushman-001 from OpenAI (the original Codex model that powered early versions of GitHub Copilot). With a context length of over 8,000 tokens, the StarCoder models can process more input than any other open LLM, enabling a wide range of interesting applications. For example, by prompting the StarCoder models with a series of dialogues, we enabled them to act as a technical assistant.Starting Price: Free -
20
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 -
21
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 -
22
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 -
23
Codestral
Mistral AI
We introduce Codestral, our first-ever code model. Codestral is an open-weight generative AI model explicitly designed for code generation tasks. It helps developers write and interact with code through a shared instruction and completion API endpoint. As it masters code and English, it can be used to design advanced AI applications for software developers. Codestral is trained on a diverse dataset of 80+ programming languages, including the most popular ones, such as Python, Java, C, C++, JavaScript, and Bash. It also performs well on more specific ones like Swift and Fortran. This broad language base ensures Codestral can assist developers in various coding environments and projects.Starting Price: Free -
24
Gemini 1.5 Flash
Google
The Gemini 1.5 Flash AI model is an advanced, high-speed language model engineered for lightning-fast processing and real-time responsiveness. Designed to excel in dynamic and time-sensitive applications, it combines streamlined neural architecture with cutting-edge optimization techniques to deliver exceptional performance without compromising on accuracy. Gemini 1.5 Flash is tailored for scenarios requiring rapid data processing, instant decision-making, and seamless multitasking, making it ideal for chatbots, customer support systems, and interactive applications. Its lightweight yet powerful design ensures it can be deployed efficiently across a range of platforms, from cloud-based environments to edge devices, enabling businesses to scale their operations with unmatched agility. -
25
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. -
26
Gemini Nano
Google
Gemini Nano from Google is a lightweight, energy-efficient AI model designed for high performance in compact, resource-constrained environments. Tailored for edge computing and mobile applications, Gemini Nano combines Google's advanced AI architecture with cutting-edge optimization techniques to deliver seamless performance without compromising speed or accuracy. Despite its compact size, it excels in tasks like voice recognition, natural language processing, real-time translation, and personalized recommendations. With a focus on privacy and efficiency, Gemini Nano processes data locally, minimizing reliance on cloud infrastructure while maintaining robust security. Its adaptability and low power consumption make it an ideal choice for smart devices, IoT ecosystems, and on-the-go AI solutions. -
27
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. -
28
Yi-Lightning
Yi-Lightning
Yi-Lightning, developed by 01.AI under the leadership of Kai-Fu Lee, represents the latest advancement in large language models with a focus on high performance and cost-efficiency. It boasts a maximum context length of 16K tokens and is priced at $0.14 per million tokens for both input and output, making it remarkably competitive. Yi-Lightning leverages an enhanced Mixture-of-Experts (MoE) architecture, incorporating fine-grained expert segmentation and advanced routing strategies, which contribute to its efficiency in training and inference. This model has excelled in various domains, achieving top rankings in categories like Chinese, math, coding, and hard prompts on the chatbot arena, where it secured the 6th position overall and 9th in style control. Its development included comprehensive pre-training, supervised fine-tuning, and reinforcement learning from human feedback, ensuring both performance and safety, with optimizations in memory usage and inference speed. -
29
YandexGPT
Yandex
Take advantage of the capabilities of generative language models to improve and optimize your applications and web services. Get an aggregated result of accumulated textual data whether it be information from work chats, user reviews, or other types of data. YandexGPT will help both summarize and interpret the information. Speed up text creation as you improve their quality and style. Create template texts for newsletters, product descriptions for online stores and other applications. Develop a chatbot for your support service: teach the bot to answer various user questions, both common and more complicated. Use the API to integrate the service with your applications and automate processes. -
30
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 -
31
JinaChat
Jina AI
Experience JinaChat, a pioneering LLM service tailored for pro users. JinaChat ushers in a new era of multimodal chat capabilities, extending beyond text to incorporate images and more. Delight in our offer of free short interactions under 100 tokens. Our API empowers developers to leverage long conversation histories and eliminate redundant prompts to build complex applications. Dive headfirst into the future of LLM services with JinaChat, where conversations are multimodal, long-memory, and affordable. Modern LLM applications often hinge on lengthy prompts or extensive memory, leading to high costs when similar prompts are repeatedly sent to the server with only minor changes. JinaChat's API solves this problem by letting you carry forward previous conversations without resending the entire prompt. This saves you both time and money, making it the perfect tool for developing complex applications like AutoGPT.Starting Price: $9.99 per month -
32
Inflection AI
Inflection AI
Inflection AI is a cutting-edge artificial intelligence research and development company focused on creating advanced AI systems designed to interact with humans in more natural, intuitive ways. Founded in 2022 by entrepreneurs such as Mustafa Suleyman, one of the co-founders of DeepMind, and Reid Hoffman, co-founder of LinkedIn, the company's mission is to make powerful AI more accessible and aligned with human values. Inflection AI specializes in building large-scale language models that enhance human-AI communication, aiming to transform industries ranging from customer service to personal productivity through intelligent, responsive, and ethically designed AI systems. The company's focus on safety, transparency, and user control ensures that their innovations contribute positively to society while addressing potential risks associated with AI technology.Starting Price: Free -
33
NVIDIA AI Foundations
NVIDIA
Impacting virtually every industry, generative AI unlocks a new frontier of opportunities, for knowledge and creative workers, to solve today’s most important challenges. NVIDIA is powering generative AI through an impressive suite of cloud services, pre-trained foundation models, as well as cutting-edge frameworks, optimized inference engines, and APIs to bring intelligence to your enterprise applications. NVIDIA AI Foundations is a set of cloud services that advance enterprise-level generative AI and enable customization across use cases in areas such as text (NVIDIA NeMo™), visual content (NVIDIA Picasso), and biology (NVIDIA BioNeMo™). Unleash the full potential with NeMo, Picasso, and BioNeMo cloud services, powered by NVIDIA DGX™ Cloud, the AI supercomputer. Marketing copy, storyline creation, and global translation in many languages. For news, email, meeting minutes, and information synthesis. -
34
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 -
35
Qwen2
Alibaba
Qwen2 is the large language model series developed by Qwen team, Alibaba Cloud. Qwen2 is a series of large language models developed by the Qwen team at Alibaba Cloud. It includes both base language models and instruction-tuned models, ranging from 0.5 billion to 72 billion parameters, and features both dense models and a Mixture-of-Experts model. The Qwen2 series is designed to surpass most previous open-weight models, including its predecessor Qwen1.5, and to compete with proprietary models across a broad spectrum of benchmarks in language understanding, generation, multilingual capabilities, coding, mathematics, and reasoning.Starting Price: Free -
36
GradientJ
GradientJ
GradientJ provides everything you need to build large language model applications in minutes and manage them forever. Discover and maintain the best prompts by saving versions and comparing them across benchmark examples. Orchestrate and manage complex applications by chaining prompts and knowledge bases into complex APIs. Enhance the accuracy of your models by integrating them with your proprietary data. -
37
Code Llama
Meta
Code Llama is a large language model (LLM) that can use text prompts to generate code. Code Llama is state-of-the-art for publicly available LLMs on code tasks, and has the potential to make workflows faster and more efficient for current developers and lower the barrier to entry for people who are learning to code. Code Llama has the potential to be used as a productivity and educational tool to help programmers write more robust, well-documented software. Code Llama is a state-of-the-art LLM capable of generating code, and natural language about code, from both code and natural language prompts. Code Llama is free for research and commercial use. Code Llama is built on top of Llama 2 and is available in three models: Code Llama, the foundational code model; Codel Llama - Python specialized for Python; and Code Llama - Instruct, which is fine-tuned for understanding natural language instructions.Starting Price: Free -
38
Jurassic-1
AI21 Labs
Jurassic-1 models come in two sizes, where the Jumbo version, at 178B parameters, is the largest and most sophisticated language model ever released for general use by developers. AI21 Studio is currently in open beta, allowing anyone to sign up and immediately start querying Jurassic-1 using our API and interactive web environment. Our mission at AI21 Labs is to fundamentally reimagine the way humans read and write by introducing machines as thought partners, and the only way we can achieve this is if we take on this challenge together. We’ve been researching language models since our Mesozoic Era (aka 2017 😉). Jurassic-1 builds on this research, and it is the first generation of models we’re making available for widespread use. -
39
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 -
40
LUIS
Microsoft
Language Understanding (LUIS): A machine learning-based service to build natural language into apps, bots, and IoT devices. Quickly create enterprise-ready, custom models that continuously improve. Add natural language to your apps. Designed to identify valuable information in conversations, LUIS interprets user goals (intents) and distills valuable information from sentences (entities), for a high quality, nuanced language model. LUIS integrates seamlessly with the Azure Bot Service, making it easy to create a sophisticated bot. Powerful developer tools are combined with customizable pre-built apps and entity dictionaries, such as Calendar, Music, and Devices, so you can build and deploy a solution more quickly. Dictionaries are mined from the collective knowledge of the web and supply billions of entries, helping your model to correctly identify valuable information from user conversations. Active learning is used to continuously improve the quality of the models. -
41
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. -
42
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 -
43
Cohere
Cohere AI
Build natural language understanding and generation into your product with a few lines of code. The Cohere API provides access to models that read billions of web pages and learn to understand the meaning, sentiment, and intent of the words we use. Use the Cohere API to write human-like text by completing a prompt or filling in blanks. You can write copy, generate code, summarize text, and more. Compute the likelihood of text and retrieve representations from the model. Use the likelihood API to filter text based on chosen categories or selected criteria. With representations, you can train your own downstream models on a wide variety of domain-specific natural language tasks. The Cohere API can compute the similarity between pieces of text, and make categorical predictions by comparing the likelihood of different text options. The model has multiple lenses through which to view ideas, so that it can recognize abstract similarities between concepts as distinct as DNA and computers.Starting Price: $0.40 / 1M Tokens -
44
PaLM
Google
PaLM API is an easy and safe way to build on top of our best language models. Today, we’re making an efficient model available, in terms of size and capabilities, and we’ll add other sizes soon. The API also comes with an intuitive tool called MakerSuite, which lets you quickly prototype ideas and, over time, will have features for prompt engineering, synthetic data generation and custom-model tuning — all supported by robust safety tools. Select developers can access the PaLM API and MakerSuite in Private Preview today, and stay tuned for our waitlist soon. -
45
Google AI Studio
Google
Google AI Studio is a free, web-based tool that allows individuals and small teams to develop apps and chatbots using natural-language prompting. It also allows users to create prompts and API keys for app development. Google AI Studio is a development environment that allows users to discover Gemini Pro APIs, create prompts, and fine-tune Gemini. It also offers a generous free quota, allowing 60 requests per minute. Google also has a Generative AI Studio, which is a product on Vertex AI. It includes models of different types, allowing users to generate content that may be text, image, or audio.Starting Price: Free -
46
Teuken 7B
OpenGPT-X
Teuken-7B is a multilingual, open source language model developed under the OpenGPT-X initiative, specifically designed to cater to Europe's diverse linguistic landscape. It has been trained on a dataset comprising over 50% non-English texts, encompassing all 24 official languages of the European Union, ensuring robust performance across these languages. A key innovation in Teuken-7B is its custom multilingual tokenizer, optimized for European languages, which enhances training efficiency and reduces inference costs compared to standard monolingual tokenizers. The model is available in two versions, Teuken-7B-Base, the foundational pre-trained model, and Teuken-7B-Instruct, which has undergone instruction tuning for improved performance in following user prompts. Both versions are accessible on Hugging Face, promoting transparency and collaboration within the AI community. The development of Teuken-7B underscores a commitment to creating AI models that reflect Europe's diversity.Starting Price: Free -
47
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 -
48
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 -
49
Gemini 1.5 Pro
Google
The Gemini 1.5 Pro AI model is a state-of-the-art language model designed to deliver highly accurate, context-aware, and human-like responses across a variety of applications. Built with cutting-edge neural architecture, it excels in natural language understanding, generation, and reasoning tasks. The model is fine-tuned for versatility, supporting tasks like content creation, code generation, data analysis, and complex problem-solving. Its advanced algorithms ensure nuanced comprehension, enabling it to adapt to different domains and conversational styles seamlessly. With a focus on scalability and efficiency, the Gemini 1.5 Pro is optimized for both small-scale implementations and enterprise-level integrations, making it a powerful tool for enhancing productivity and innovation. -
50
Mistral 7B
Mistral AI
Mistral 7B is a 7.3-billion-parameter language model that outperforms larger models like Llama 2 13B across various benchmarks. It employs Grouped-Query Attention (GQA) for faster inference and Sliding Window Attention (SWA) to efficiently handle longer sequences. Released under the Apache 2.0 license, Mistral 7B is accessible for deployment across diverse platforms, including local environments and major cloud services. Additionally, a fine-tuned version, Mistral 7B Instruct, demonstrates enhanced performance in instruction-following tasks, surpassing models like Llama 2 13B Chat.Starting Price: Free