Alternatives to ESMFold
Compare ESMFold alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to ESMFold in 2026. Compare features, ratings, user reviews, pricing, and more from ESMFold 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. -
2
Google AI Studio
Google
Google AI Studio is a unified development platform that helps teams explore, build, and deploy applications using Google’s most advanced AI models, including Gemini 3. It brings text, image, audio, and video models together in one interactive playground. With vibe coding, developers can use natural language to quickly turn ideas into working AI applications. The platform reduces friction by generating functional apps that are ready for deployment with minimal setup. Built-in integrations like Google Search enhance real-world use cases. Google AI Studio also centralizes API key management, usage monitoring, and billing. It offers a fast, intuitive path from prompt to production powered by vibe coding workflows. -
3
LM-Kit.NET
LM-Kit
LM-Kit.NET is a cutting-edge, high-level inference SDK designed specifically to bring the advanced capabilities of Large Language Models (LLM) into the C# ecosystem. Tailored for developers working within .NET, LM-Kit.NET provides a comprehensive suite of powerful Generative AI tools, making it easier than ever to integrate AI-driven functionality into your applications. The SDK is versatile, offering specialized AI features that cater to a variety of industries. These include text completion, Natural Language Processing (NLP), content retrieval, text summarization, text enhancement, language translation, and much more. Whether you are looking to enhance user interaction, automate content creation, or build intelligent data retrieval systems, LM-Kit.NET offers the flexibility and performance needed to accelerate your project. -
4
GeoMx Digital Spatial Profiler (DSP)
nanoString
Quickly resolve tissue heterogeneity and the complexity of microenvironments with the GeoMx Digital Spatial Profiler (DSP), the most flexible and robust spatial multi-omic platform for analysis of FFPE and fresh frozen tissue sections. GeoMx is the only spatial biology platform that non-destructively profiles the expression of RNA and protein from distinct tissue compartments and cell populations with an automated and scalable workflow that integrates with standard histology staining. Spatially profile the whole transcriptome and 570+ protein targets separately or simultaneously from your choice of sample inputs: whole tissue sections, tissue microarrays (TMAs), or organoids. Make GeoMx DSP your spatial biology platform of choice for biomarker discovery and hypothesis testing. Decide where to draw the line and let the tissue be your guide with biology-driven profiling that empowers you to choose the tissue microenvironments and cell types that matter most to you. -
5
GPT-3.5
OpenAI
GPT-3.5 is the next evolution of GPT 3 large language model from OpenAI. GPT-3.5 models can understand and generate natural language. We offer four main models with different levels of power suitable for different tasks. The main GPT-3.5 models are meant to be used with the text completion endpoint. We also offer models that are specifically meant to be used with other endpoints. Davinci is the most capable model family and can perform any task the other models can perform and often with less instruction. For applications requiring a lot of understanding of the content, like summarization for a specific audience and creative content generation, Davinci is going to produce the best results. These increased capabilities require more compute resources, so Davinci costs more per API call and is not as fast as the other models.Starting Price: $0.0200 per 1000 tokens -
6
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 -
7
GPT-4o
OpenAI
GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time (opens in a new window) in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.Starting Price: $5.00 / 1M tokens -
8
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 -
9
GPT-3
OpenAI
Our GPT-3 models can understand and generate natural language. We offer four main models with different levels of power suitable for different tasks. Davinci is the most capable model, and Ada is the fastest. The main GPT-3 models are meant to be used with the text completion endpoint. We also offer models that are specifically meant to be used with other endpoints. Davinci is the most capable model family and can perform any task the other models can perform and often with less instruction. For applications requiring a lot of understanding of the content, like summarization for a specific audience and creative content generation, Davinci is going to produce the best results. These increased capabilities require more compute resources, so Davinci costs more per API call and is not as fast as the other models.Starting Price: $0.0200 per 1000 tokens -
10
ERNIE Bot
Baidu
ERNIE Bot is an AI-powered conversational assistant developed by Baidu, designed to facilitate seamless and natural interactions with users. Built on the ERNIE (Enhanced Representation through Knowledge Integration) model, ERNIE Bot excels at understanding complex queries and generating human-like responses across various domains. Its capabilities include processing text, generating images, and engaging in multimodal communication, making it suitable for a wide range of applications such as customer support, virtual assistants, and enterprise automation. With its advanced contextual understanding, ERNIE Bot offers an intuitive and efficient solution for businesses seeking to enhance their digital interactions and automate workflows.Starting Price: Free -
11
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. -
12
Gopher
Google DeepMind
Language, and its role in demonstrating and facilitating comprehension - or intelligence - is a fundamental part of being human. It gives people the ability to communicate thoughts and concepts, express ideas, create memories, and build mutual understanding. These are foundational parts of social intelligence. It’s why our teams at DeepMind study aspects of language processing and communication, both in artificial agents and in humans. As part of a broader portfolio of AI research, we believe the development and study of more powerful language models – systems that predict and generate text – have tremendous potential for building advanced AI systems that can be used safely and efficiently to summarise information, provide expert advice and follow instructions via natural language. Developing beneficial language models requires research into their potential impacts, including the risks they pose. -
13
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 -
14
BLOOM
BigScience
BLOOM is an autoregressive Large Language Model (LLM), trained to continue text from a prompt on vast amounts of text data using industrial-scale computational resources. As such, it is able to output coherent text in 46 languages and 13 programming languages that is hardly distinguishable from text written by humans. BLOOM can also be instructed to perform text tasks it hasn't been explicitly trained for, by casting them as text generation tasks. -
15
Gemini 2.0
Google
Gemini 2.0 is an advanced AI-powered model developed by Google, designed to offer groundbreaking capabilities in natural language understanding, reasoning, and multimodal interactions. Building on the success of its predecessor, Gemini 2.0 integrates large language processing with enhanced problem-solving and decision-making abilities, enabling it to interpret and generate human-like responses with greater accuracy and nuance. Unlike traditional AI models, Gemini 2.0 is trained to handle multiple data types simultaneously, including text, images, and code, making it a versatile tool for research, business, education, and creative industries. Its core improvements include better contextual understanding, reduced bias, and a more efficient architecture that ensures faster, more reliable outputs. Gemini 2.0 is positioned as a major step forward in the evolution of AI, pushing the boundaries of human-computer interaction.Starting Price: Free -
16
XLNet
XLNet
XLNet is a new unsupervised language representation learning method based on a novel generalized permutation language modeling objective. Additionally, XLNet employs Transformer-XL as the backbone model, exhibiting excellent performance for language tasks involving long context. Overall, XLNet achieves state-of-the-art (SOTA) results on various downstream language tasks including question answering, natural language inference, sentiment analysis, and document ranking.Starting Price: Free -
17
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. -
18
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 -
19
ERNIE 5.0
Baidu
ERNIE 5.0 is a next-generation conversational AI platform developed by Baidu, designed to deliver natural, human-like interactions across multiple domains. Built on Baidu’s Enhanced Representation through Knowledge Integration (ERNIE) framework, it fuses advanced natural language processing (NLP) with deep contextual understanding. The model supports multimodal capabilities, allowing it to process and generate text, images, and voice seamlessly. ERNIE 5.0’s refined contextual awareness enables it to handle complex conversations with greater precision and nuance. Its applications span customer service, content generation, and enterprise automation, enhancing both user engagement and productivity. With its robust architecture, ERNIE 5.0 represents a major step forward in Baidu’s pursuit of intelligent, knowledge-driven AI systems. -
20
BERT
Google
BERT is a large language model and a method of pre-training language representations. Pre-training refers to how BERT is first trained on a large source of text, such as Wikipedia. You can then apply the training results to other Natural Language Processing (NLP) tasks, such as question answering and sentiment analysis. With BERT and AI Platform Training, you can train a variety of NLP models in about 30 minutes.Starting Price: Free -
21
Octave TTS
Hume AI
Hume AI has introduced Octave (Omni-capable Text and Voice Engine), a groundbreaking text-to-speech system that leverages large language model technology to understand and interpret the context of words, enabling it to generate speech with appropriate emotions, rhythm, and cadence, unlike traditional TTS models that merely read text, Octave acts akin to a human actor, delivering lines with nuanced expression based on the content. Users can create diverse AI voices by providing descriptive prompts, such as "a sarcastic medieval peasant," allowing for tailored voice generation that aligns with specific character traits or scenarios. Additionally, Octave offers the flexibility to modify the emotional delivery and speaking style through natural language instructions, enabling commands like "sound more enthusiastic" or "whisper fearfully" to fine-tune the output.Starting Price: $3 per month -
22
ERNIE X1
Baidu
ERNIE X1 is an advanced conversational AI model developed by Baidu as part of their ERNIE (Enhanced Representation through Knowledge Integration) series. Unlike previous versions, ERNIE X1 is designed to be more efficient in understanding and generating human-like responses. It incorporates cutting-edge machine learning techniques to handle complex queries, making it capable of not only processing text but also generating images and engaging in multimodal communication. ERNIE X1 is often used in natural language processing applications such as chatbots, virtual assistants, and enterprise automation, offering significant improvements in accuracy, contextual understanding, and response quality.Starting Price: $0.28 per 1M tokens -
23
OpenAI
OpenAI
OpenAI’s mission is to ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity. We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome. Apply our API to any language task — semantic search, summarization, sentiment analysis, content generation, translation, and more — with only a few examples or by specifying your task in English. One simple integration gives you access to our constantly-improving AI technology. Explore how you integrate with the API with these sample completions. -
24
AI21 Studio
AI21 Studio
AI21 Studio provides API access to Jurassic-1 large-language-models. Our models power text generation and comprehension features in thousands of live applications. Take on any language task. Our Jurassic-1 models are trained to follow natural language instructions and require just a few examples to adapt to new tasks. Use our specialized APIs for common tasks like summarization, paraphrasing and more. Access superior results at a lower cost without reinventing the wheel. Need to fine-tune your own custom model? You're just 3 clicks away. Training is fast, affordable and trained models are deployed immediately. Give your users superpowers by embedding an AI co-writer in your app. Drive user engagement and success with features like long-form draft generation, paraphrasing, repurposing and custom auto-complete.Starting Price: $29 per month -
25
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. -
26
Azure OpenAI Service
Microsoft
Apply advanced coding and language models to a variety of use cases. Leverage large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. Gain access to generative models that have been pretrained with trillions of words. Apply them to new scenarios including language, code, reasoning, inferencing, and comprehension. Customize generative models with labeled data for your specific scenario using a simple REST API. Fine-tune your model's hyperparameters to increase accuracy of outputs. Use the few-shot learning capability to provide the API with examples and achieve more relevant results.Starting Price: $0.0004 per 1000 tokens -
27
DeepSeek-V3
DeepSeek
DeepSeek-V3 is a state-of-the-art AI model designed to deliver unparalleled performance in natural language understanding, advanced reasoning, and decision-making tasks. Leveraging next-generation neural architectures, it integrates extensive datasets and fine-tuned algorithms to tackle complex challenges across diverse domains such as research, development, business intelligence, and automation. With a focus on scalability and efficiency, DeepSeek-V3 provides developers and enterprises with cutting-edge tools to accelerate innovation and achieve transformative outcomes.Starting Price: Free -
28
Grok 4
xAI
Grok 4 is the latest AI model from Elon Musk’s xAI, marking a significant advancement in AI reasoning and natural language understanding. Developed on the Colossus supercomputer, Grok 4 supports multimodal inputs including text and images, with plans to add video capabilities soon. It features enhanced precision in language tasks and has demonstrated superior performance in scientific reasoning and visual problem-solving compared to other leading AI models. Designed for developers, researchers, and technical users, Grok 4 offers powerful tools for complex tasks. The model incorporates improved moderation to address previous concerns about biased or problematic outputs. Grok 4 represents a major leap forward in AI’s ability to understand and generate human-like responses. -
29
Grok 4.1
xAI
Grok 4.1 is an advanced AI model developed by Elon Musk’s xAI, designed to push the limits of reasoning and natural language understanding. Built on the powerful Colossus supercomputer, it processes multimodal inputs including text and images, with upcoming support for video. The model delivers exceptional accuracy in scientific, technical, and linguistic tasks. Its architecture enables complex reasoning and nuanced response generation that rivals the best AI systems in the world. Enhanced moderation ensures more responsible and unbiased outputs than earlier versions. Grok 4.1 is a breakthrough in creating AI that can think, interpret, and respond more like a human. -
30
Llama
Meta
Llama (Large Language Model Meta AI) is a state-of-the-art foundational large language model designed to help researchers advance their work in this subfield of AI. Smaller, more performant models such as Llama enable others in the research community who don’t have access to large amounts of infrastructure to study these models, further democratizing access in this important, fast-changing field. Training smaller foundation models like Llama is desirable in the large language model space because it requires far less computing power and resources to test new approaches, validate others’ work, and explore new use cases. Foundation models train on a large set of unlabeled data, which makes them ideal for fine-tuning for a variety of tasks. We are making Llama available at several sizes (7B, 13B, 33B, and 65B parameters) and also sharing a Llama model card that details how we built the model in keeping with our approach to Responsible AI practices. -
31
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 -
32
SnapGene
SnapGene
Accurately design and simulate cloning procedures. Test complicated projects, catch errors before they happen, and obtain the right constructs the first time. Cloning is easier when you can see what you are doing. The intuitive interface offers you unparalleled visibility into your work, simplifying often complex tasks. SnapGene automates documentation, so you don’t have to. See and share every sequence edit and cloning procedure that led to your final plasmid. Improve your core molecular biology procedures, and improve your results. Master SnapGene and key concepts in cloning with our new online learning center, SnapGene Academy. Containing over 50 video tutorials taught by scientific experts, SnapGene Academy helps you advance your skills across multiple molecular biology courses. SnapGene 7.2 provides a new visualization of primer homodimer structures and enhancements to file management, allowing tabs to be organized in multiple windows using drag and drop.Starting Price: $295 per year -
33
Giga ML
Giga ML
We just launched X1 large series of Models. Giga ML's most powerful model is available for pre-training and fine-tuning with on-prem deployment. Since we are Open AI compatible, your existing integrations with long chain, llama-index, and all others work seamlessly. You can continue pre-training of LLM's with domain-specific data books or docs or company docs. The world of large language models (LLMs) rapidly expanding, offering unprecedented opportunities for natural language processing across various domains. However, some critical challenges have remained unaddressed. At Giga ML, we proudly introduce the X1 Large 32k model, a pioneering on-premise LLM solution that addresses these critical issues. -
34
Partek Flow
Partek
Partek bioinformatics software delivers powerful statistical and visualization tools in an easy-to-use interface. Researchers of all skill levels are empowered to explore genomic data quicker and easier than ever before. We turn data into discovery®. Pre-installed workflows and pipelines in our intuitive point-and-click interface make sophisticated NGS and array analysis attainable for any scientist. Custom and public statistical algorithms work in concert to easily and precisely distill NGS data into biological insights. Genome browser, Venn diagrams, heat maps, and other interactive visualizations reveal the biology of your next-generation sequencing and array data in brilliant color. Our Ph.D. scientists are always just a phone call away and ready to help with your NGS analysis any time you have questions. Designed specifically for the compute-intensive needs of next-generation sequencing applications with flexible installation and user management options. -
35
FutureHouse
FutureHouse
FutureHouse is a nonprofit AI research lab focused on automating scientific discovery in biology and other complex sciences. FutureHouse features superintelligent AI agents designed to assist scientists in accelerating research processes. It is optimized for retrieving and summarizing information from scientific literature, achieving state-of-the-art performance on benchmarks like RAG-QA Arena's science benchmark. It employs an agentic approach, allowing for iterative query expansion, LLM re-ranking, contextual summarization, and document citation traversal to enhance retrieval accuracy. FutureHouse also offers a framework for training language agents on challenging scientific tasks, enabling agents to perform tasks such as protein engineering, literature summarization, and molecular cloning. Their LAB-Bench benchmark evaluates language models on biology research tasks, including information extraction, database retrieval, etc. -
36
RoBERTa
Meta
RoBERTa builds on BERT’s language masking strategy, wherein the system learns to predict intentionally hidden sections of text within otherwise unannotated language examples. RoBERTa, which was implemented in PyTorch, modifies key hyperparameters in BERT, including removing BERT’s next-sentence pretraining objective, and training with much larger mini-batches and learning rates. This allows RoBERTa to improve on the masked language modeling objective compared with BERT and leads to better downstream task performance. We also explore training RoBERTa on an order of magnitude more data than BERT, for a longer amount of time. We used existing unannotated NLP datasets as well as CC-News, a novel set drawn from public news articles.Starting Price: Free -
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
Medical LLM
John Snow Labs
John Snow Labs' Medical LLM is an advanced, domain-specific large language model (LLM) designed to revolutionize the way healthcare organizations harness the power of artificial intelligence. This innovative platform is tailored specifically for the healthcare industry, combining cutting-edge natural language processing (NLP) capabilities with a deep understanding of medical terminology, clinical workflows, and regulatory requirements. The result is a powerful tool that enables healthcare providers, researchers, and administrators to unlock new insights, improve patient outcomes, and drive operational efficiency. At the heart of the Healthcare LLM is its comprehensive training on vast amounts of healthcare data, including clinical notes, research papers, and regulatory documents. This specialized training allows the model to accurately interpret and generate medical text, making it an invaluable asset for tasks such as clinical documentation, automated coding, and medical research. -
39
Cellenics
Biomage
Turn your single-cell RNA sequencing data into meaningful insight with Cellenics software. Biomage hosts a community instance of Cellenics, an open source analytics tool for single-cell RNA sequencing data that has been developed at Harvard Medical School. It enables biologists to explore single-cell datasets without writing code and helps scientists and bioinformaticians to work together more effectively. It takes you from count matrices to publication-ready figures in just a few hours and can be integrated seamlessly with your workflow. It’s fast, interactive, and user-friendly. And it’s cloud-based, secure, and scaleable. The Biomage-hosted community instance of Cellenics is free for academic researchers with small/medium-sized datasets (up to 500,000 cells). It’s used by 3000+ academic researchers studying cancer, cardiovascular health, and developmental biology.Starting Price: Free -
40
Claude Pro
Anthropic
Claude Pro is an advanced large language model designed to handle complex tasks while maintaining a friendly, accessible demeanor. Trained on extensive, high-quality data, it excels at understanding context, interpreting subtle nuances, and producing well-structured, coherent responses across a wide range of topics. By leveraging robust reasoning capabilities and a refined knowledge base, Claude Pro can draft detailed reports, compose creative content, summarize lengthy documents, and even assist in coding tasks. Its adaptive algorithms continuously improve its ability to learn from feedback, ensuring that its output remains accurate, reliable, and helpful. Whether serving professionals seeking expert support or individuals looking for quick, informative answers, Claude Pro delivers a versatile and productive conversational experience.Starting Price: $18/month -
41
ERNIE 4.5
Baidu
ERNIE 4.5 is a cutting-edge conversational AI platform developed by Baidu, leveraging advanced natural language processing (NLP) models to enable highly sophisticated human-like interactions. The platform is part of Baidu’s ERNIE (Enhanced Representation through Knowledge Integration) series, which integrates multimodal capabilities, including text, image, and voice. ERNIE 4.5 enhances the ability of AI models to understand complex context and deliver more accurate, nuanced responses, making it suitable for various applications, from customer service and virtual assistants to content creation and enterprise-level automation.Starting Price: $0.55 per 1M tokens -
42
Evo 2
Arc Institute
Evo 2 is a genomic foundation model capable of generalist prediction and design tasks across DNA, RNA, and proteins. It utilizes a frontier deep learning architecture to model biological sequences at single-nucleotide resolution, achieving near-linear scaling of compute and memory relative to context length. Trained with 40 billion parameters and a 1 megabase context length, Evo 2 processes over 9 trillion nucleotides from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function prediction across multiple biological modalities, including DNA, RNA, and proteins, and to generate novel sequences with plausible genomic architecture. The model's capabilities have been demonstrated in tasks such as designing functional CRISPR systems and predicting disease-causing mutations in human genes. Evo 2 is publicly accessible via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework. -
43
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 -
44
Cufflinks
Cole Trapnell
Cufflinks assemble transcripts, estimate their abundances and test for differential expression and regulation in RNA-Seq samples. It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts. Cufflinks then estimates the relative abundances of these transcripts based on how many reads support each one, taking into account biases in library preparation protocols. Cufflinks was originally developed as part of a collaborative effort between the Laboratory for Mathematical and Computational Biology. In order to make it easy to install Cufflinks, we provide a few binary packages to save users from the occasionally frustrating process of building Cufflinks, which requires that you install the libraries. Cufflinks includes a number of tools for analyzing RNA-Seq experiments. Some of these tools can be run on their own, while others are pieces of a larger workflow.Starting Price: Free -
45
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 -
46
CodeGemma
Google
CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following. CodeGemma has 3 model variants, a 7B pre-trained variant that specializes in code completion and generation from code prefixes and/or suffixes, a 7B instruction-tuned variant for natural language-to-code chat and instruction following; and a state-of-the-art 2B pre-trained variant that provides up to 2x faster code completion. Complete lines, and functions, and even generate entire blocks of code, whether you're working locally or using Google Cloud resources. Trained on 500 billion tokens of primarily English language data from web documents, mathematics, and code, CodeGemma models generate code that's not only more syntactically correct but also semantically meaningful, reducing errors and debugging time. -
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Gemini Advanced
Google
Gemini Advanced is a cutting-edge AI model designed for unparalleled performance in natural language understanding, generation, and problem-solving across diverse domains. Featuring a revolutionary neural architecture, it delivers exceptional accuracy, nuanced contextual comprehension, and deep reasoning capabilities. Gemini Advanced is engineered to handle complex, multifaceted tasks, from creating detailed technical content and writing code to conducting in-depth data analysis and providing strategic insights. Its adaptability and scalability make it a powerful solution for both individual users and enterprise-level applications. Gemini Advanced sets a new standard for intelligence, innovation, and reliability in AI-powered solutions. You'll also get access to Gemini in Gmail, Docs, and more, 2 TB storage, and other benefits from Google One. Gemini Advanced also offers access to Gemini with Deep Research. You can conduct in-depth and real-time research on almost any subject.Starting Price: $19.99 per month -
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Grok 4.20
xAI
Grok 4.20 is an advanced artificial intelligence model developed by xAI to elevate reasoning and natural language understanding. Built on the high-performance Colossus supercomputer, it is engineered for speed, scale, and accuracy. Grok 4.20 processes multimodal inputs such as text and images, with video support planned for future releases. The model excels in scientific, technical, and linguistic tasks, delivering highly precise and context-aware responses. Its architecture supports deep reasoning and sophisticated problem-solving capabilities. Enhanced moderation improves output reliability and reduces bias compared to earlier versions. Overall, Grok 4.20 represents a significant step toward more human-like AI reasoning and interpretation. -
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Alpa
Alpa
Alpa aims to automate large-scale distributed training and serving with just a few lines of code. Alpa was initially developed by folks in the Sky Lab, UC Berkeley. Some advanced techniques used in Alpa have been written in a paper published in OSDI'2022. Alpa community is growing with new contributors from Google. A language model is a probability distribution over sequences of words. It predicts the next word based on all the previous words. It is useful for a variety of AI applications, such the auto-completion in your email or chatbot service. For more information, check out the language model wikipedia page. GPT-3 is very large language model, with 175 billion parameters, that uses deep learning to produce human-like text. Many researchers and news articles described GPT-3 as "one of the most interesting and important AI systems ever produced". GPT-3 is gradually being used as a backbone in the latest NLP research and applications.Starting Price: Free -
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Adept
Adept
Adept is an ML research and product lab building general intelligence by enabling humans and computers to work together creatively. Designed and trained specifically for taking actions on computers in response to your natural language commands. ACT-1 is our first step towards a foundation model that can use every software tool, API and website that exists. Adept is building an entirely new way to get things done. It takes your goals, in plain language, and turns them into actions on the software you use every day. We believe that AI systems should be built with users at the center — where machines work together with people in the driver's seat, discovering new solutions, enabling more informed decisions, and giving us more time for the work we love.
