Alternatives to ESMFold2
Compare ESMFold2 alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to ESMFold2 in 2026. Compare features, ratings, user reviews, pricing, and more from ESMFold2 competitors and alternatives in order to make an informed decision for your business.
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1
Biohub
Biohub
Biohub is an open platform for building on the world model of protein biology. It provides access to the ESM family of models, including ESMC, ESMFold2, and ESM3, along with interactive tools and developer resources for protein science research. ESMC is a state-of-the-art protein language model trained on billions of evolutionary sequences, building representations that capture fundamental mechanisms of protein structure and function. It powers functional analysis, structure prediction, protein design, and the exploration of evolutionary relationships between proteins. ESMFold2 predicts high-resolution, all-atom 3D structures of biomolecular complexes directly from sequence, with optional multiple sequence alignment input for enhanced accuracy on challenging targets. ESM3 jointly models sequence, structure, and function, enabling controllable generation of novel proteins by conditioning on any combination of these modalities. -
2
ESMC
Biohub
ESMC is the latest in the ESM family of protein language models, establishing a new frontier in representation learning for protein biology. Trained on billions of evolutionary sequences, it learns representations that reflect a mechanistic reduction of protein structure and function. The model is built on a transformer architecture, supports sequences as its core modality, and is trained on up to 6 billion proteins. ESMC is designed for protein science research, including structure prediction, function annotation, protein design, and understanding evolutionary relationships between proteins. It can generate novel proteins from partial sequence, structure, or functional constraints, helping researchers explore new possibilities in protein design and biological discovery. The Biohub Platform provides access to ESMC through the API and the ESM Python package, with quickstart resources for installing the package, creating an API key, connecting to the platform.Starting Price: Free -
3
NVIDIA 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. -
4
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. -
5
HyperProtein
Hypercube
HyperProtein is Hypercube, Inc.'s new product focusing on the computational science associated with protein sequences. The product includes the analysis of one-dimensional protein sequences as well as the analysis of consequent three-dimensional protein structures. In particular, the relationship between sequence and structure is a fundamental facet of the product. Unlike individual software programs that provide capability for some aspect of protein sequence or structure, such as sequence alignment, HyperProtein puts together a multitude of Bioinformatics and Molecular Modeling tools related to the science that initiates with a protein sequence. -
6
Swiss-PdbViewer
Swiss-PdbViewer
Swiss-PdbViewer (aka DeepView) is an application that provides a user-friendly interface allowing to analysis of several proteins at the same time. The proteins can be superimposed in order to deduce structural alignments and compare their active sites or any other relevant parts. Amino acid mutations, H-bonds, angles, and distances between atoms are easy to obtain thanks to the intuitive graphic and menu interface. Swiss-PdbViewer (aka DeepView) has been developed since 1994 by Nicolas Guex. Swiss-PdbViewer was initially tightly linked to SWISS-MODEL, an automated homology modeling server developed within the Swiss Institute of Bioinformatics (SIB) at the Structural Bioinformatics Group at the Biozentrum in Basel. However, the SWISS-MODEL web interface evolved to a point where it is now possible to use it directly for advanced modeling. Maintaining a direct interface with Swiss-PdbViewer is too complex and no longer supported. -
7
AlphaFold
DeepMind
These exquisite, intricate machines are proteins. They underpin not just the biological processes in your body but every biological process in every living thing. They’re the building blocks of life. Currently, there are around 100 million known distinct proteins, with many more found every year. Each one has a unique 3D shape that determines how it works and what it does. But figuring out the exact structure of a protein remains an expensive and often time-consuming process, meaning we only know the exact 3D structure of a tiny fraction of the proteins known to science. Finding a way to close this rapidly expanding gap and predict the structure of millions of unknown proteins could not only help us tackle disease and more quickly find new medicines but perhaps also unlock the mysteries of how life itself works. -
8
3decision
Discngine
3decision® is a cloud-based protein structure repository designed for comprehensive structural data management and advanced analytics, enabling small molecule and biologics discovery teams to accelerate structure-based drug design. It centralizes and standardizes experimental and in-silico protein structures from public sources like RCSB PDB and AlphaFoldDB, as well as proprietary data, supporting formats like PDBx/mmCIF and ModelCIF. This ensures easy access to X-Ray, NMR, cryo-EM, and modeled structures, fostering collaboration and enhancing research efforts. Beyond storage, 3decision® enriches entries with metadata and sequence information, including protein-ligand interactions, antibody annotations, and binding site details. Advanced analytical tools identify druggable sites, assess off-target risks, and enable binding site comparisons, transforming vast structural data into actionable knowledge. Its cloud-based platform facilitates collaboration among research teams. -
9
GPT-Rosalind
OpenAI
GPT-Rosalind is a purpose-built frontier reasoning model developed by OpenAI to accelerate scientific research across biology, drug discovery, and translational medicine. It is designed specifically for life sciences workflows, where researchers must navigate large volumes of literature, experimental data, and specialized databases to generate and validate new ideas. It combines deep domain understanding in areas such as chemistry, genomics, protein engineering, and disease biology with advanced tool-use capabilities, allowing it to interact with scientific databases, analyze experimental outputs, and support complex, multi-step reasoning tasks. It can assist with evidence synthesis, hypothesis generation, literature review, sequence interpretation, and experimental planning, helping scientists move faster from raw data to actionable insights. GPT-Rosalind transforms complex, time-intensive research processes into more efficient AI-assisted workflows. -
10
Evo Designer
Arc Institute
Evo Designer is an advanced tool developed by the Arc Institute, leveraging the capabilities of the Evo 2 genomic foundation model to facilitate DNA sequence generation and analysis. This platform enables users to input nucleotide sequences or specify organisms, prompting the model to generate corresponding DNA sequences. It provides comprehensive annotations of coding regions and, for prokaryotic sequences, offers 3D protein visualizations utilizing ESMFold. Additionally, Evo Designer evaluates sequences by scoring their perplexity and per-nucleotide entropy, assisting researchers in assessing sequence complexity and variability. The underlying Evo 2 model is trained on over 9 trillion nucleotides from a diverse array of prokaryotic and eukaryotic genomes, employing a deep learning architecture that models biological sequences at single-nucleotide resolution with a context window extending up to 1 million tokens. -
11
LigPlot+
EMBL-EBI
LigPlot+ is a successor to our original LIGPLOT program for the automatic generation of 2D ligand-protein interaction diagrams. It is run from an intuitive java interface that allows on-screen editing of the plots via mouse click-and-drag operations. In addition to the new interface, the program includes several major enhancements over the old version. When two or more ligand-protein complexes are sufficiently similar, LigPlot+ can automatically display their interaction diagrams either superposed or side by side. Any conserved interactions are highlighted. The LigPlot+ suite also now includes an update of the original DIMPLOT program for plotting protein-protein or domain-domain interactions. Users can flexibly select the interface of interest and DIMPLOT will then generate a diagram showing the residue-residue interactions across the interface. To assist in interpretation, the residues in one of the interfaces can be optionally displayed in sequence order. -
12
AutoDock
AutoDock
AutoDock is a suite of automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. Over the years, it has been modified and improved to add new functionalities, and multiple engines have been developed. Current distributions of AutoDock consist of two generations of software: AutoDock 4 and AutoDock Vina. More recently, we developed AutoDock-GPU, an accelerated version of AutoDock4 that is hundreds of times faster than the original single-CPU docking code. AutoDock 4 actually consists of two main programs: autodock performs the docking of the ligand to a set of grids describing the target protein; autogrid pre-calculates these grids. In addition to using them for docking, the atomic affinity grids can be visualized. This can help, for example, to guide organic synthetic chemists design better binders. -
13
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. -
14
Profluent
Profluent
Profluent's platform revolutionizes protein design by integrating advanced AI with in-house wet-lab capabilities, enabling the creation of proteins either inspired by nature or reimagined from scratch. This holistic approach allows for precise, adaptable, and scalable solutions to complex biological challenges, delivering results that redefine what's possible with proteins. Profluent's foundation models push the frontier of protein design beyond the limitations of random discovery, facilitating the optimization of multiple attributes simultaneously, accessing greater sequence diversity, and enabling novel functionalities. By extrapolating into new protein spaces, Profluent offers unique possibilities beyond natural or patented proteins, making it cheaper, easier, and feasible for partners to achieve commercial success. Profluent's capabilities are built on a commitment to scientific rigor, leveraging diverse datasets and advanced AI to tackle challenges. -
15
Muse
Microsoft
Microsoft has unveiled Muse, a groundbreaking generative AI model designed to revolutionize gameplay ideation. Developed in collaboration with Ninja Theory, Muse is a World and Human Action Model (WHAM) trained on data from the game Bleeding Edge. This AI model possesses a comprehensive understanding of 3D game environments, including physics and player interactions, enabling it to generate consistent and diverse gameplay sequences. Muse can produce game visuals and predict controller actions, facilitating rapid prototyping and creative exploration for game developers. By analyzing over 1 billion images and actions, Muse demonstrates the potential to assist in game preservation by recreating classic titles for modern platforms. While still in the early stages, with current outputs at a resolution of 300×180 pixels, Muse represents a significant advancement in integrating AI into the game development process, aiming to enhance, not replace, human creativity. -
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AudioLM
Google
AudioLM is a pure audio language model that generates high‑fidelity, long‑term coherent speech and piano music by learning from raw audio alone, without requiring any text transcripts or symbolic representations. It represents audio hierarchically using two types of discrete tokens, semantic tokens extracted from a self‑supervised model to capture phonetic or melodic structure and global context, and acoustic tokens from a neural codec to preserve speaker characteristics and fine waveform details, and chains three Transformer stages to predict first semantic tokens for high‑level structure, then coarse and finally fine acoustic tokens for detailed synthesis. The resulting pipeline allows AudioLM to condition on a few seconds of input audio and produce seamless continuations that retain voice identity, prosody, and recording conditions in speech or melody, harmony, and rhythm in music. Human evaluations show that synthetic continuations are nearly indistinguishable from real recordings. -
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NVIDIA Parabricks
NVIDIA
NVIDIA® Parabricks® is the only GPU-accelerated suite of genomic analysis applications that delivers fast and accurate analysis of genomes and exomes for sequencing centers, clinical teams, genomics researchers, and high-throughput sequencing instrument developers. NVIDIA Parabricks provides GPU-accelerated versions of tools used every day by computational biologists and bioinformaticians—enabling significantly faster runtimes, workflow scalability, and lower compute costs. From FastQ to Variant Call Format (VCF), NVIDIA Parabricks accelerates runtimes across a series of hardware configurations with NVIDIA A100 Tensor Core GPUs. Genomic researchers can experience acceleration across every step of their analysis workflows, from alignment to sorting to variant calling. When more GPUs are used, a near-linear scaling in compute time is observed compared to CPU-only systems, allowing up to 107X acceleration. -
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Orbit BioSequence
Questel
Orbit BioSequence by Questel is a powerful IP intelligence software specifically designed to help researchers, patent professionals, and biotech companies analyze and manage biological sequence data within the intellectual property (IP) landscape. It offers an advanced solution for searching, analyzing, and monitoring nucleotide and protein sequences found in patent documents, giving users unprecedented access to sequence information critical for innovation and competitive analysis. Orbit BioSequence allows users to perform highly accurate similarity and identity searches across global patent databases, helping organizations identify existing patents, avoid infringement risks, and uncover licensing or partnership opportunities. It also integrates cutting-edge search algorithms and curated datasets to ensure precision and relevance in search results. -
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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 -
20
NVIDIA PhysicsNeMo
NVIDIA
NVIDIA PhysicsNeMo is an open source Python deep-learning framework for building, training, fine-tuning, and inferring physics-AI models that combine physics knowledge with data to accelerate simulations, create high-fidelity surrogate models, and enable near-real-time predictions across domains such as computational fluid dynamics, structural mechanics, electromagnetics, weather and climate, and digital twin applications. It provides scalable, GPU-accelerated tools and Python APIs built on PyTorch and released under the Apache 2.0 license, offering curated model architectures including physics-informed neural networks, neural operators, graph neural networks, and generative AI–based approaches so developers can harness physics-driven causality alongside observed data for engineering-grade modeling. PhysicsNeMo includes end-to-end training pipelines from geometry ingestion to differential equations, reference application recipes to jump-start workflows.Starting Price: Free -
21
Rebot
Retransform
Rebot is a Robotic Process Automation (RPA) service dedicated to the real estate industry. RPA technology works by mimicking the human actions which are repetitive and predictive, completing the otherwise manual tasks in no time at all. Not only does Rebot enable a much faster and virtual workforce, but it also reduces the probability of human error. Using Machine Learning, our Rebots can execute a structured sequence of steps, leading to meaningful and accurate activity without human intervention. -
22
Alchemite
Intellegens
Alchemite provides AI-augmented physical modeling and solutions that help organizations extract actionable insights from experimental and simulation data by combining machine learning with physics-informed models to improve prediction accuracy, reduce experimental costs, and optimize product and process development. Its solutions span materials discovery and design, predictive modelling of performance and reliability, multiscale modelling that connects atomistic to macroscopic behaviour, and automation of workflow tasks such as data integration, surrogate modelling, and model validation. It supports physics-aware neural networks and hybrid modelling approaches that respect underlying scientific laws while learning from data to enable faster and more accurate simulations, reduced reliance on expensive physical testing, and improved decision-making. Intellegens’ tools are applied in areas such as battery performance prediction, chemical process optimization, etc. -
23
ALBERT
Google
ALBERT is a self-supervised Transformer model that was pretrained on a large corpus of English data. This means it does not require manual labelling, and instead uses an automated process to generate inputs and labels from raw texts. It is trained with two distinct objectives in mind. The first is Masked Language Modeling (MLM), which randomly masks 15% of words in the input sentence and requires the model to predict them. This technique differs from RNNs and autoregressive models like GPT as it allows the model to learn bidirectional sentence representations. The second objective is Sentence Ordering Prediction (SOP), which entails predicting the ordering of two consecutive segments of text during pretraining. -
24
Hunyuan Motion 1.0
Tencent Hunyuan
Hunyuan Motion (also known as HY-Motion 1.0) is a state-of-the-art text-to-3D motion generation AI model that uses a billion-parameter Diffusion Transformer with flow matching to turn natural language prompts into high-quality, skeleton-based 3D character animation in seconds. It understands descriptive text in English and Chinese and produces smooth, physically plausible motion sequences that integrate seamlessly into standard 3D animation pipelines by exporting to skeleton formats such as SMPL or SMPLH and common formats like FBX or BVH for use in Blender, Unity, Unreal Engine, Maya, and other tools. The model’s three-stage training pipeline (large-scale pre-training on thousands of hours of motion data, fine-tuning on curated sequences, and reinforcement learning from human feedback) enhances its ability to follow complex instructions and generate realistic, temporally coherent motion. -
25
GLM-OCR
Z.ai
GLM-OCR is a multimodal optical character recognition model and open source repository that provides accurate, efficient, and comprehensive document understanding by combining text and visual modalities into a unified encoder–decoder architecture derived from the GLM-V family. Built with a visual encoder pre-trained on large-scale image–text data and a lightweight cross-modal connector feeding into a GLM-0.5B language decoder, the model supports layout detection, parallel region recognition, and structured output for text, tables, formulas, and complicated real-world document formats. It introduces Multi-Token Prediction (MTP) loss and stable full-task reinforcement learning to improve training efficiency, recognition accuracy, and generalization, achieving state-of-the-art benchmarks on major document understanding tasks.Starting Price: Free -
26
LTX-2.3
Lightricks
LTX-2.3 is an advanced AI video generation model designed to create high-quality videos from text prompts, images, or other media inputs while maintaining strong control over motion, structure, and audiovisual synchronization. It is part of the LTX family of multimodal generative models built for developers and production teams that need scalable tools to generate and edit video programmatically. It builds on the capabilities of earlier LTX models by improving detail rendering, motion consistency, prompt understanding, and audio quality throughout the video generation pipeline. It features a redesigned latent representation using an upgraded VAE trained on higher-quality datasets, which improves the preservation of fine textures, edges, and small visual elements such as hair, text, and intricate surfaces across frames.Starting Price: Free -
27
VeraChem
VeraChem
VeraChem LLC was founded in 2000 to advance the state of the art in computer-aided drug discovery and molecular design by developing computational chemistry methods that are based on cutting-edge basic science but are also applicable in applied science research settings. Efficient high-performance software implementations of these methods coupled with comprehensive user support are a central company strategy for product development. Current VeraChem software capabilities include protein-ligand and host-guest binding affinity prediction, fast calculation of accurate partial atomic charges for drug-like compounds, computation of energies and forces with all the commonly used empirical force fields, automatic generation of alternate resonance forms of drug-like compounds, conformational search with the powerful Tork algorithm, and automatic detection of topological and 3D molecular symmetries. VeraChem’s software packages are constructed from a modular code base. -
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BIOVIA Materials Studio
Dassault Systèmes
BIOVIA Materials Studio is a comprehensive modeling and simulation environment designed to enable researchers in materials science and chemistry to predict and understand the relationships between a material’s atomic and molecular structure and its properties and behavior. Utilizing an "in silico first" approach allows for the optimization of material performance in a cost-effective virtual setting prior to physical testing. It supports a wide range of materials, including catalysts, polymers, composites, metals, alloys, pharmaceuticals, batteries, and more. It offers tools for quantum, atomistic, mesoscale, statistical, analytical, and crystallization simulations, facilitating the design of advanced materials across various industries. Features include the ability to accelerate innovation, reduce R&D costs through virtual screening, and improve efficiency by automating best practices within Pipeline Pilot. -
29
BenevolentAI
BenevolentAI
BenevolentAI is an AI-enabled drug discovery platform and scientific technology company that unites advanced artificial intelligence, machine learning, and domain-specific science to accelerate the discovery, design, and development of new medicines for complex diseases by making sense of vast, diverse biomedical data and generating actionable scientific insights faster than traditional methods. Its proprietary Benevolent Platform ingests and harmonizes structured and unstructured biomedical information, including literature, genomics, clinical information, and multi-omics data, into a comprehensive knowledge graph, enabling scientists to reason across biological systems, generate hypotheses, predict novel drug targets, and design candidate molecules with higher confidence and lower failure rates. -
30
MEGA
MEGA
MEGA (Molecular Evolutionary Genetics Analysis) is a powerful and user-friendly software suite designed for analyzing DNA and protein sequence data from species and populations. It facilitates both automatic and manual sequence alignment, phylogenetic tree inference, and evolutionary hypothesis testing. MEGA supports a variety of statistical methods including maximum likelihood, Bayesian inference, and ordinary least squares, making it an essential tool for comparative sequence analysis and understanding molecular evolution. MEGA offers advanced features such as real-time caption generation to help explain the results and methods used in analysis and the maximum composite likelihood method for estimating evolutionary distances. The software is equipped with robust visual tools like the alignment/trace editor and tree explorer and supports multi-threading for efficient processing. MEGA can be run on multiple operating systems, including Windows, Linux, and macOS.Starting Price: Free -
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ResoluteAI
ResoluteAI
ResoluteAI's secure platform lets you search aggregated scientific, regulatory, and business databases simultaneously. Combined with our interactive analytics and downloadable visualizations, you can make connections that lead to breakthrough discoveries. Nebula is ResoluteAI's enterprise search product for science. We apply structured metadata and a range of AI capabilities to your institutional knowledge. This includes NLP, OCR, image recognition, and transcription, making your proprietary information easily findable and accessible. With Nebula, you have the power to unlock the hidden value in your research, experiments, market intelligence, and acquired assets. Structured metadata created from unstructured text, semantic expansion, conceptual search, and document similarity search. -
32
Seed-Music
ByteDance
Seed-Music is a unified framework for high-quality and controlled music generation and editing, capable of producing vocal and instrumental works from multimodal inputs such as lyrics, style descriptions, sheet music, audio references, or voice prompts, and of supporting post-production editing of existing tracks by allowing direct modification of melodies, timbres, lyrics, or instruments. It combines autoregressive language modeling with diffusion approaches and a three-stage pipeline comprising representation learning (which encodes raw audio into intermediate representations, including audio tokens, symbolic music tokens, and vocoder latents), generation (which transforms these multimodal inputs into music representations), and rendering (which converts those representations into high-fidelity audio). The system supports lead-sheet to song conversion, singing synthesis, voice conversion, audio continuation, style transfer, and fine-grained control over music structure. -
33
AskPaper
AskPaper
Ask Paper allows you to read and extract information from papers more quickly. It allows you to upload papers either by URL or by uploading a PDF file, and then ask natural language questions about the paper. AskPaper is a tool powered by a Large Language Model. This is a Neural Network that was trained on a lot of internet text to understand how the language works, all by trying to predict the next word in a sequence. By feeding the paper contents and the query to the models, it will try to "predict" a plausible answer. All you have to do is register in discord and join our server. If you need further help, login as a guest, and there's in an option to receive instructions via email on how to use the tool. -
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OpenAI deep research
OpenAI
OpenAI's deep research is an AI-powered tool designed to autonomously conduct complex, multi-step research tasks across various domains, such as science, coding, and mathematics. By analyzing user-provided inputs—such as questions, text documents, images, PDFs, or spreadsheets—the system formulates a structured research plan, gathers relevant information, and delivers comprehensive responses within minutes. It also provides process summaries with citations, helping users verify sources. While this tool significantly accelerates research efficiency, it may occasionally produce inaccuracies or struggle to differentiate between authoritative sources and misinformation. Currently available to ChatGPT Pro users, deep research represents a step toward AI-driven knowledge discovery, with ongoing improvements planned for accuracy and response time. -
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Qwen3-VL
Alibaba
Qwen3-VL is the newest vision-language model in the Qwen family (by Alibaba Cloud), designed to fuse powerful text understanding/generation with advanced visual and video comprehension into one unified multimodal model. It accepts inputs in mixed modalities, text, images, and video, and handles long, interleaved contexts natively (up to 256 K tokens, with extensibility beyond). Qwen3-VL delivers major advances in spatial reasoning, visual perception, and multimodal reasoning; the model architecture incorporates several innovations such as Interleaved-MRoPE (for robust spatio-temporal positional encoding), DeepStack (to leverage multi-level features from its Vision Transformer backbone for refined image-text alignment), and text–timestamp alignment (for precise reasoning over video content and temporal events). These upgrades enable Qwen3-VL to interpret complex scenes, follow dynamic video sequences, read and reason about visual layouts.Starting Price: Free -
36
Geneious
Geneious
Geneious Prime makes bioinformatics accessible by transforming raw data into visualizations that make sequence analysis intuitive and user-friendly. Simple sequence assembly and easy editing of contigs. Automatic annotation for gene prediction, motifs, translation, and variant calling. Genotype microsatellite traces with automated ladder fitting and peak calling and generates tables of alleles. Beautiful visualizations of annotated genomes and assemblies are displayed in a highly customizable sequence view. Powerful SNP variants analysis, simple RNA-Seq expression analysis, and amplicon metagenomics. Design and test PCR and sequencing primers and create your own searchable primer database. Geneious Biologics is a flexible, scalable, and secure way to streamline your antibody analysis workflows, create high-quality libraries and select the optimal therapeutic candidates.Starting Price: $1,280 per year -
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Seed3D
ByteDance
Seed3D 1.0 is a foundation-model pipeline that takes a single input image and generates a simulation-ready 3D asset, including closed manifold geometry, UV-mapped textures, and physically-based rendering material maps, designed for immediate integration into physics engines and embodied-AI simulators. It uses a hybrid architecture combining a 3D variational autoencoder for latent geometry encoding, and a diffusion-transformer stack to generate detailed 3D shapes, followed by multi-view texture synthesis, PBR material estimation, and UV texture completion. The geometry branch produces watertight meshes with fine structural details (e.g., thin protrusions, holes, text), while the texture/material branch yields multi-view consistent albedo, metallic, and roughness maps at high resolution, enabling realistic appearance under varied lighting. Assets generated by Seed3D 1.0 require minimal cleanup or manual tuning. -
38
XYZ
XYZ Reality
The Atom is a powerful, custom-built engineering tool combining a construction safety headset, augmented reality displays and in-built computing power. With the Atom, construction teams can view and position holograms of 3D design models to millimeter accuracy onsite. With The Atom, construction teams can view 3D models with millimeter accuracy onsite. The Atom’s controller is used to interact with the AR interface. The controller’s ergonomic design and comfort grip ensure the user is always focused on the task at hand. The Atom positions 3D design models to millimeter accuracy with its laser-based tracking technology. The models are positioned in absolute terms by physically tapping into the site coordinate system. Users can walk through construction sites viewing holograms of models positioned within construction tolerances. The Atom enables an efficient way of working bridging data flow between teams. -
39
AudioCraft
Meta AI
AudioCraft is a single-stop code base for all your generative audio needs: music, sound effects, and compression after training on raw audio signals. With AudioCraft, we simplify the overall design of generative models for audio compared to prior work. Both MusicGen and AudioGen consist of a single autoregressive Language Model (LM) that operates over streams of compressed discrete music representation, i.e., tokens. We introduce a simple approach to leverage the internal structure of the parallel streams of tokens and show that, with a single model and elegant token interleaving pattern, our approach efficiently models audio sequences, simultaneously capturing the long-term dependencies in the audio and allowing us to generate high-quality audio. Our models leverage the EnCodec neural audio codec to learn the discrete audio tokens from the raw waveform. EnCodec maps the audio signal to one or several parallel streams of discrete tokens. -
40
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. -
41
VeChain
VeChain
The public blockchain that derives its value from activities created by members within the ecosystem solving real world economic problems. With BlockRef and Expiration transaction fields, users can set the time when transaction is processed or expired if not being included in a block. Flexible transaction fee delegation schemes (Multi-party Payment and Designated Gas Payer) enable a freemium model within a decentralized application to onboard users without friction. Multi-function atomic transactions allow developers to batch payments, add multiple calls to different contract functions into one transaction and determine their sequence. Set dependencies to ensure the execution order meets the business need, transactions that specify a dependency will not be executed until the required transaction is processed. -
42
Simufact Welding
Hexagon
Simufact Welding is a modular product line, which offers comprehensive functionality for modeling the elastic-plastic behavior of materials and structural welding simulation. The software covers different welding processes. Simufact Welding is designed for modeling and simulation of a wide range of thermal joining processes by means of structural welding simulation including usual arc and beam welding processes as well as brazing. Additionally, Simufact Welding provides possibilities to model heat treatment processes, variations of cooling and unclamping setups as well as mechanical loading of welded structures. Identify critical distortions, i.e. with respect to assembly, bulging, imbalances, and clearances. Investigate and optimize clamping tools even before an investment in tools has been made. Identify optimal welding directions and welding sequences. -
43
Tangent Works
Tangent Works
Drive business value from predictive analytics. Make informed decisions and improve processes. Create predictive models in seconds for faster and better forecasting & anomaly detection. TIM InstantML is a hyper-automated, augmented machine learning solution for time series data for better, faster, and more accurate forecasting, anomaly detection, and classification. TIM helps you to discover the business value of your data and enables you to leverage the power of predictive analytics. High-quality automatic feature engineering while simultaneously adapting the model structure and model parameters. TIM offers flexible deployment options. Easy integration with some of your favorite platforms. TIM offers a wide array of interfaces. Users looking for a streamlined graphical interface can find this in TIM Studio. Become truly data-driven with powerful, automated predictive analytics. Discover the predictive value in your data faster and easier.Starting Price: €3.20 per month -
44
Gemini Diffusion
Google DeepMind
Gemini Diffusion is our state-of-the-art research model exploring what diffusion means for language and text generation. Large-language models are the foundation of generative AI today. We’re using a technique called diffusion to explore a new kind of language model that gives users greater control, creativity, and speed in text generation. Diffusion models work differently. Instead of predicting text directly, they learn to generate outputs by refining noise, step by step. This means they can iterate on a solution very quickly and error correct during the generation process. This helps them excel at tasks like editing, including in the context of math and code. Generates entire blocks of tokens at once, meaning it responds more coherently to a user’s prompt than autoregressive models. Gemini Diffusion’s external benchmark performance is comparable to much larger models, whilst also being faster. -
45
Cora SeQuence
Genpact
Orchestrate a more effective flow of work with Cora SeQuence. Generate growth, improve cost efficiency, and drive business agility. Our HotChange® technology lets end users see how they're employing resources and processing performance. Make real-time changes to get the most from business-critical processes. Design advanced customer workflows with an intuitive interface. Reduce pain points and transform the customer experience with our SeQuence CRM edition that has solutions for a wide range of industries. Model, configure, run, monitor, and transform end-to-end business processes with our simple drag-and-drop functionality. Predictive analytics and connectors for robotic automation, artificial intelligence, and the internet of things help digitize any business process. -
46
Seedream 4.0
ByteDance
Seedream 4.0 is a next-generation multimodal AI image generation and editing model that unifies text-to-image creation and text-guided image editing within a single architecture, delivering professional-grade visuals up to 4K resolution with exceptional fidelity and speed. It’s built around an efficient diffusion transformer and variational autoencoder design that lets it interpret text prompts and reference images to produce highly detailed, consistent outputs while handling complex semantics, lighting, and structure reliably, and it offers batch generation, multi-reference support, and precise control over edits such as style, background, or object changes without degrading the rest of the scene. Seedream 4.0 demonstrates industry-leading prompt understanding, aesthetic quality, and structural stability across generation and editing tasks, outperforming earlier versions and rival models in benchmarks for prompt adherence and visual coherence. -
47
Seedance 1.5 pro
ByteDance
Seedance 1.5 Pro is a next-generation AI audio-video generation model developed by ByteDance’s Seed research team that produces native, synchronized video and sound in a single unified pass from text prompts and image or visual inputs, eliminating the traditional need to create visuals first and add audio later. It features joint audio-visual generation with highly accurate lip-sync and motion alignment, supporting multilingual audio and spatial sound effects that match the visuals for immersive storytelling and dialogue, and it maintains visual consistency and cinematic motion across multi-shot sequences including camera moves and narrative continuity. Able to generate short clips (typically 4–12 seconds) in up to 1080p quality with expressive motion, stable aesthetics, and optional first- and last-frame control, the model works for both text-to-video and image-to-video workflows so creators can animate static images or build full cinematic sequences with coherent narrative flow. -
48
HyperX
Collier Aerospace
Collier Aerospace develops HyperX, a computer-aided engineering software suite for structural analysis, design optimization, and lightweighting of aerospace and high-performance composite and metallic structures. HyperX provides engineers with an automated framework to perform classical and advanced failure analyses with margin-of-safety reporting across hundreds of analytical methods and thousands of finite element analysis load cases, then sizes structural elements to find the lightest manufacturable combination of materials, panel geometries, layup ply angles, and stacking sequences. It integrates with users’ preferred FEA and CAD tools, updating optimized panel and joint designs directly in both FEM and CAD models and maintaining a consistent digital thread from concept through certification. HyperX’s capabilities include stress analysis, sizing optimization, producibility evaluation, certification-ready reporting, data traceability, and trend dashboards. -
49
Gemini 3 Deep Think
Google
The most advanced model from Google DeepMind, Gemini 3, sets a new bar for model intelligence by delivering state-of-the-art reasoning and multimodal understanding across text, image, and video. It surpasses its predecessor on key AI benchmarks and excels at deeper problems such as scientific reasoning, complex coding, spatial logic, and visual-/video-based understanding. The new “Deep Think” mode pushes the boundaries even further, offering enhanced reasoning for very challenging tasks, outperforming Gemini 3 Pro on benchmarks like Humanity’s Last Exam and ARC-AGI. Gemini 3 is now available across Google’s ecosystem, enabling users to learn, build, and plan at new levels of sophistication. With context windows up to one million tokens, more granular media-processing options, and specialized configurations for tool use, the model brings better precision, depth, and flexibility for real-world workflows. -
50
ROCKITPLAY
DacsLabs
ROCKITPLAY delivers data differently than a standard game download or file load. Instead of downloading files in an arbitrary sequence, ROCKITPLAY sequences data based on real user gameplay, so that the data blocks that are required in the first minutes of gameplay are delivered first. FastStart downloads can start a game with as little as 1% downloaded. ROCKITPLAY dynamically adjusts the time to start based on the game and available user bandwidth. Start playing games up to 200x faster while downloading. Reduce patch sizes by up to 50% saving bandwidth and costs. Increase reading speed of HDD to greater than SSD speed. Based on real user behavior the system intelligently predicts required data blocks in order to start the game during download. With ROCKITPLAY, the game is being downloaded in data-sequenced order, so at the end you have a full, standard game install. Data remains sequenced even on your local drive, significantly improving game boot and loading time.
