Alternatives to PanGu-α
Compare PanGu-α alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to PanGu-α in 2026. Compare features, ratings, user reviews, pricing, and more from PanGu-α competitors and alternatives in order to make an informed decision for your business.
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1
Parallels RAS
Parallels
Parallels® Remote Application Server (RAS) is a remote work solution that provides secure virtual access to business applications and desktops on any device or OS—from anywhere. The platform offers an agile, cloud-ready foundation and end-to-end security fueled by a centralized management console with granular policies. Companies can leverage on-premises, hybrid, or public cloud deployments and integrate with existing technology like Microsoft Azure and AWS. Parallels RAS aims to give organizations the flexibility, scalability, and IT agility to adapt to changing business needs. Parallels RAS offers a single, full-featured licensing model that includes 24/7 support and access to product training.Starting Price: $120 US/year/concurrent user -
2
Salesfinity
Salesfinity
Engage in endless live customer conversations on the phone and leave the busywork to the Salesfinity AI parallel dialer. Automate manual dialing with a smart parallel dialer while avoiding bad numbers and VMs. Let Salesfinity AI score your lead list and smartly prioritize parallel dialing for more successful connections. Salesfinity intelligently manages your caller IDs for optimal call reputation. Salesfinity is the best-in-class parallel dialer that integrates with all popular CRMs and SEPs. Discover how effortlessly the Salesfinity parallel dialer blends into your sales routine, as intuitive as playing your favorite tune. Everything you need to scale your outbound calling. Effortlessly sync calls to your CRM and amplifies your sales productivity with Salesfinity. Navigate with ease through Salesfinity's clear, user-friendly interface. Invest in success with clear, value-driven plans that amplify your team's performance, leveraging the power of a parallel dialer.Starting Price: $149 per month -
3
BLACKBOX AI
BLACKBOX AI
BLACKBOX AI is an advanced AI-powered platform designed to accelerate coding, app development, and deep research tasks. It features an AI Coding Agent that supports real-time voice interaction, GPU acceleration, and remote parallel task execution. Users can convert Figma designs into functional code and transform images into web applications with minimal coding effort. The platform enables screen sharing within IDEs like VSCode and offers mobile access to coding agents. BLACKBOX AI also supports integration with GitHub repositories for streamlined remote workflows. Its capabilities extend to website design, app building with PDF context, and image generation and editing.Starting Price: Free -
4
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. -
5
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. -
6
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 -
7
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 -
8
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. -
9
LAMMPS
LAMMPS
LAMMPS, the Large-scale Atomic/Molecular Massively Parallel Simulator, is a classical molecular dynamics code with a focus on materials modeling. It models ensembles of particles in liquid, solid, or gaseous states and can simulate atomic, polymeric, biological, solid-state, granular, coarse-grained, mesoscopic, or macroscopic systems using many interatomic potentials, force fields, and boundary conditions. LAMMPS can model systems in two or three dimensions, from only a few particles up to billions, and is designed to run efficiently on parallel computers while remaining easy to extend and modify. It includes potentials for solid-state materials such as metals and semiconductors, soft matter such as biomolecules and polymers, and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generally, as a parallel particle simulator at atomic, meso, or continuum scale.Starting Price: Free -
10
DeepSpeed
Microsoft
DeepSpeed is an open source deep learning optimization library for PyTorch. It's designed to reduce computing power and memory use, and to train large distributed models with better parallelism on existing computer hardware. DeepSpeed is optimized for low latency, high throughput training. DeepSpeed can train DL models with over a hundred billion parameters on the current generation of GPU clusters. It can also train up to 13 billion parameters in a single GPU. DeepSpeed is developed by Microsoft and aims to offer distributed training for large-scale models. It's built on top of PyTorch, which specializes in data parallelism.Starting Price: Free -
11
Parallel AI
Parallel AI
Meet Parallel AI—a cutting-edge solution tailored for modern businesses. With Parallel AI, select the most suitable AI model for each specific task, ensuring unparalleled efficiency and accuracy. Our platform seamlessly integrates with your existing knowledge bases, creating AI employees who are informed and ready to tackle your business challenges. Whether it's conducting robust research projects swiftly or providing expert consultations on-demand, Parallel AI equips your business with virtual experts to chat with anytime, anywhere. Uncapped access to the top AI models available today. Use the model that works best with your data and your business. Easily upload business documents to train your AI employees.Starting Price: $29 per month -
12
OpenCL
The Khronos Group
OpenCL (Open Computing Language) is an open, royalty-free standard for cross-platform parallel programming of heterogeneous computing systems that lets developers accelerate computing tasks by leveraging diverse processors such as CPUs, GPUs, DSPs, and FPGAs across supercomputers, cloud servers, personal computers, mobile devices, and embedded platforms. It defines a programming framework including a C-based language for writing compute kernels and a runtime API to control devices, manage memory, and execute parallel code, giving portable and efficient access to heterogeneous hardware. OpenCL improves speed and responsiveness for a wide range of applications including creative tools, scientific and medical software, vision processing, and neural network training and inferencing by offloading compute-intensive work to accelerator processors. -
13
GPT-J
EleutherAI
GPT-J is a cutting-edge language model created by the research organization EleutherAI. In terms of performance, GPT-J exhibits a level of proficiency comparable to that of OpenAI's renowned GPT-3 model in a range of zero-shot tasks. Notably, GPT-J has demonstrated the ability to surpass GPT-3 in tasks related to generating code. The latest iteration of this language model, known as GPT-J-6B, is built upon a linguistic dataset referred to as The Pile. This dataset, which is publicly available, encompasses a substantial volume of 825 gibibytes of language data, organized into 22 distinct subsets. While GPT-J shares certain capabilities with ChatGPT, it is important to note that GPT-J is not designed to operate as a chatbot; rather, its primary function is to predict text. In a significant development in March 2023, Databricks introduced Dolly, a model that follows instructions and is licensed under Apache.Starting Price: Free -
14
Orpheus TTS
Canopy Labs
Canopy Labs has introduced Orpheus, a family of state-of-the-art speech large language models (LLMs) designed for human-level speech generation. These models are built on the Llama-3 architecture and are trained on over 100,000 hours of English speech data, enabling them to produce natural intonation, emotion, and rhythm that surpasses current state-of-the-art closed source models. Orpheus supports zero-shot voice cloning, allowing users to replicate voices without prior fine-tuning, and offers guided emotion and intonation control through simple tags. The models achieve low latency, with approximately 200ms streaming latency for real-time applications, reducible to around 100ms with input streaming. Canopy Labs has released both pre-trained and fine-tuned 3B-parameter models under the permissive Apache 2.0 license, with plans to release smaller models of 1B, 400M, and 150M parameters for use on resource-constrained devices. -
15
Gaia
Gaia
Train, deploy, and commercialize your neural machine translator with just a few clicks, no coding required. Upload your parallel data CSV file with a simple drag-and-drop interface. Fine-tune your model with advanced settings for optimal performance. Start training instantly with our powerful NVIDIA GPU infrastructure. Train models for a wide range of language pairs, including low-resource languages. Track training progress and performance metrics in real time. Easily integrate your trained model with our comprehensive API. Configure your model parameters and hyperparameters. Upload your parallel data CSV file to the dashboard. Review training metrics and BLEU scores. Use your deployed model via dashboard or API. Click "start training" and let our GPUs do the work. It's often beneficial to start with default values and then experiment with different configurations. Keep track of your experiments and their results to find the optimal settings for your specific translation task. -
16
Zero Parallel
Zero Parallel
Zero Parallel is the leading digital marketing network and prides itself in exceptional lead quality, robust platform, unparalleled compliance, and excellent customer service. Zero Parallel’s personnel and technology have significantly contributed to its ongoing success within the industry. The team at Zero Parallel is committed to your success. Innovating the future of online lead generation by developing industry-leading technology that produces the greatest value for your traffic. Our vast network enables both Affiliates and Advertisers to expand their marketing opportunities and boost their bottom lines. Elevate your business model and increase your conversion rates with powerful lead management tools and top-of-the-line tracking technology. Delivering high-converting web traffic for your business - the only traffic you won’t mind. It’s our expertise, drive, and commitment to innovation that keeps us ahead of the curve. -
17
Claude Opus 4.8
Anthropic
Claude Opus 4.8 is a powerful AI model from Anthropic designed to deliver stronger coding, reasoning, agentic workflows, and advanced collaboration capabilities for developers, enterprises, and AI-powered productivity tasks. The model builds on Claude Opus 4.7 with improvements across coding benchmarks, practical knowledge work, alignment, and reliability while maintaining the same pricing structure. Claude Opus 4.8 introduces enhanced honesty and reasoning behavior, making it less likely to generate unsupported claims or overlook flaws during complex tasks such as software development and agent execution. The release also includes new features such as effort control settings, fast mode for lower-cost high-speed processing, and dynamic workflows in Claude Code that allow the system to coordinate hundreds of parallel subagents for large-scale tasks.Starting Price: $5 per 1M (input) -
18
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 -
19
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. -
20
GPT-4 Turbo
OpenAI
GPT-4 is a large multimodal model (accepting text or image inputs and outputting text) that can solve difficult problems with greater accuracy than any of our previous models, thanks to its broader general knowledge and advanced reasoning capabilities. GPT-4 is available in the OpenAI API to paying customers. Like gpt-3.5-turbo, GPT-4 is optimized for chat but works well for traditional completions tasks using the Chat Completions API. GPT-4 is the latest GPT-4 model with improved instruction following, JSON mode, reproducible outputs, parallel function calling, and more. Returns a maximum of 4,096 output tokens. This preview model is not yet suited for production traffic.Starting Price: $0.0200 per 1000 tokens -
21
CodeGeeX
AMiner
We introduce CodeGeeX, a large-scale multilingual code generation model with 13 billion parameters, pre-trained on a large code corpus of more than 20 programming languages. Based on CodeGeeX, we develop a VS Code extension (search 'CodeGeeX' in the Extension Marketplace) that assists the programming of different programming languages. Besides the multilingual code generation/translation abilities, we turn CodeGeeX into a custom programming assistant using its few-shot ability. It means that when a few examples are provided as extra prompts in the input, CodeGeeX will imitate what are done by these examples and generate codes accordingly. Some cool features can be implemented using this ability, like code explanation, summarization, generation with specific coding style, and more. For example, one can add code snippets with his/her own coding style, and CodeGeeX will generate codes in a similar way. You can also try prompts with specific formats to inspire CodeGeeX for new skills.Starting Price: Free -
22
AWS ParallelCluster
Amazon
AWS ParallelCluster is an open-source cluster management tool that simplifies the deployment and management of High-Performance Computing (HPC) clusters on AWS. It automates the setup of required resources, including compute nodes, a shared filesystem, and a job scheduler, supporting multiple instance types and job submission queues. Users can interact with ParallelCluster through a graphical user interface, command-line interface, or API, enabling flexible cluster configuration and management. The tool integrates with job schedulers like AWS Batch and Slurm, facilitating seamless migration of existing HPC workloads to the cloud with minimal modifications. AWS ParallelCluster is available at no additional charge; users only pay for the AWS resources consumed by their applications. With AWS ParallelCluster, you can use a simple text file to model, provision, and dynamically scale the resources needed for your applications in an automated and secure manner. -
23
GPT-4o mini
OpenAI
A small model with superior textual intelligence and multimodal reasoning. GPT-4o mini enables a broad range of tasks with its low cost and latency, such as applications that chain or parallelize multiple model calls (e.g., calling multiple APIs), pass a large volume of context to the model (e.g., full code base or conversation history), or interact with customers through fast, real-time text responses (e.g., customer support chatbots). Today, GPT-4o mini supports text and vision in the API, with support for text, image, video and audio inputs and outputs coming in the future. The model has a context window of 128K tokens, supports up to 16K output tokens per request, and has knowledge up to October 2023. Thanks to the improved tokenizer shared with GPT-4o, handling non-English text is now even more cost effective. -
24
GPT-5 pro
OpenAI
GPT-5 Pro is OpenAI’s most advanced AI model, designed to tackle the most complex and challenging tasks with extended reasoning capabilities. It builds on GPT-5’s unified architecture, using scaled, efficient parallel compute to provide highly comprehensive and accurate responses. GPT-5 Pro achieves state-of-the-art performance on difficult benchmarks like GPQA, excelling in areas such as health, science, math, and coding. It makes significantly fewer errors than earlier models and delivers responses that experts find more relevant and useful. The model automatically balances quick answers and deep thinking, allowing users to get expert-level insights efficiently. GPT-5 Pro is available to Pro subscribers and powers some of the most demanding applications requiring advanced intelligence. -
25
Muse Spark
Meta
Muse Spark is a multimodal AI reasoning model developed by Meta as part of its push toward personal superintelligence. It integrates text, images, and tools to deliver advanced reasoning and interactive capabilities. The model supports features like visual chain-of-thought and multi-agent orchestration. Users can leverage Muse Spark for tasks such as problem-solving, content creation, and real-world troubleshooting. Its Contemplating mode enables multiple AI agents to reason in parallel for improved performance. Muse Spark also demonstrates strong capabilities in areas like health insights and visual understanding. Overall, it represents a significant step toward more intelligent and personalized AI systems. -
26
Entry Point AI
Entry Point AI
Entry Point AI is the modern AI optimization platform for proprietary and open source language models. Manage prompts, fine-tunes, and evals all in one place. When you reach the limits of prompt engineering, it’s time to fine-tune a model, and we make it easy. Fine-tuning is showing a model how to behave, not telling. It works together with prompt engineering and retrieval-augmented generation (RAG) to leverage the full potential of AI models. Fine-tuning can help you to get better quality from your prompts. Think of it like an upgrade to few-shot learning that bakes the examples into the model itself. For simpler tasks, you can train a lighter model to perform at or above the level of a higher-quality model, greatly reducing latency and cost. Train your model not to respond in certain ways to users, for safety, to protect your brand, and to get the formatting right. Cover edge cases and steer model behavior by adding examples to your dataset.Starting Price: $49 per month -
27
Pavilion HyperOS
Pavilion
Powering the most performant, dense, scalable, and flexible storage platform in the universe. Pavilion HyperParallel File System™ provides the ability to scale across an unlimited number of Pavilion HyperParallel Flash Arrays™, providing 1.2 TB/s read, and 900 GB/s write bandwidth with 200M IOPS at 25µs latency per rack. Uniquely capable of providing independent, linear scalability of both capacity and performance, the Pavilion HyperOS 3 now provides global namespace support for both NFS and S3, enabling unlimited, linear scale across an unlimited number of Pavilion HyperParallel Flash Array systems. Take advantage of the power of the Pavilion HyperParallel Flash Array to enjoy unrivaled levels of performance and availability. The Pavilion HyperOS includes patent-pending technology to ensure that your data is always available, with performant access that legacy arrays cannot match. -
28
NAMD
Theoretical and Computational Biophysics Group
NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. Based on Charm++ parallel objects, it scales from desktop and laptop computers to high-end parallel platforms, hundreds of cores for typical simulations, and beyond 500,000 cores for the largest simulations. NAMD is built for researchers who need to simulate large molecular systems efficiently while preserving compatibility with widely used molecular modeling workflows. It uses the popular molecular graphics program VMD for simulation setup and trajectory analysis, and it is file-compatible with AMBER, CHARMM, and X-PLOR. It is designed to support biomolecular simulations involving proteins, membranes, nucleic acids, solvents, ions, and other molecular systems where atomic interactions and time-dependent motion need to be studied in detail.Starting Price: Free -
29
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. -
30
CUDA
NVIDIA
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions in the form of a few basic keywords. The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.Starting Price: Free -
31
ChatGLM
Zhipu AI
ChatGLM-6B is an open-source, Chinese-English bilingual dialogue language model based on the General Language Model (GLM) architecture with 6.2 billion parameters. Combined with model quantization technology, users can deploy locally on consumer-grade graphics cards (only 6GB of video memory is required at the INT4 quantization level). ChatGLM-6B uses technology similar to ChatGPT, optimized for Chinese Q&A and dialogue. After about 1T identifiers of Chinese and English bilingual training, supplemented by supervision and fine-tuning, feedback self-help, human feedback reinforcement learning and other technologies, ChatGLM-6B with 6.2 billion parameters has been able to generate answers that are quite in line with human preferences.Starting Price: Free -
32
Ansys HPC
Ansys
With the Ansys HPC software suite, you can use today’s multicore computers to perform more simulations in less time. These simulations can be bigger, more complex and more accurate than ever using high-performance computing (HPC). The various Ansys HPC licensing options let you scale to whatever computational level of simulation you require, from single-user or small user group options for entry-level parallel processing up to virtually unlimited parallel capacity. For large user groups, Ansys facilitates highly scalable, multiple parallel processing simulations for the most challenging projects when needed. Apart from parallel computing, Ansys also offers solutions for parametric computing, which enables you to more fully explore the design parameters (size, weight, shape, materials, mechanical properties, etc.) of your product early in the development process. -
33
MiMo-V2-Flash
Xiaomi Technology
MiMo-V2-Flash is an open weight large language model developed by Xiaomi based on a Mixture-of-Experts (MoE) architecture that blends high performance with inference efficiency. It has 309 billion total parameters but activates only 15 billion active parameters per inference, letting it balance reasoning quality and computational efficiency while supporting extremely long context handling, for tasks like long-document understanding, code generation, and multi-step agent workflows. It incorporates a hybrid attention mechanism that interleaves sliding-window and global attention layers to reduce memory usage and maintain long-range comprehension, and it uses a Multi-Token Prediction (MTP) design that accelerates inference by processing batches of tokens in parallel. MiMo-V2-Flash delivers very fast generation speeds (up to ~150 tokens/second) and is optimized for agentic applications requiring sustained reasoning and multi-turn interactions.Starting Price: Free -
34
Muse Spark 1.1
Meta
Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs built for agentic tasks, coding, computer use, tool use, and multimodal understanding. The model improves on the original Muse Spark with stronger performance in planning, orchestration, long-context work, coding workflows, and external app interactions. Muse Spark 1.1 can manage a 1 million token context window, remember earlier actions, retrieve important information, compact context, and delegate tasks across parallel subagents. It is designed to operate across tools, MCP servers, custom skills, browsers, native apps, scripts, images, video, PDFs, and audio-based workflows. Developers can access Muse Spark 1.1 through the new Meta Model API public preview, while users can try it in Thinking mode in the Meta AI app and on meta.ai.Starting Price: $1.25 per 1M tokens (input) -
35
Qwen Code
Qwen
Qwen3‑Coder is an agentic code model available in multiple sizes, led by the 480B‑parameter Mixture‑of‑Experts variant (35B active) that natively supports 256K‑token contexts (extendable to 1M) and achieves state‑of‑the‑art results on Agentic Coding, Browser‑Use, and Tool‑Use tasks comparable to Claude Sonnet 4. Pre‑training on 7.5T tokens (70 % code) and synthetic data cleaned via Qwen2.5‑Coder optimized both coding proficiency and general abilities, while post‑training employs large‑scale, execution‑driven reinforcement learning and long‑horizon RL across 20,000 parallel environments to excel on multi‑turn software‑engineering benchmarks like SWE‑Bench Verified without test‑time scaling. Alongside the model, the open source Qwen Code CLI (forked from Gemini Code) unleashes Qwen3‑Coder in agentic workflows with customized prompts, function calling protocols, and seamless integration with Node.js, OpenAI SDKs, and more.Starting Price: Free -
36
DocumentIQ
DocumentIQ
DocumentIQ extracts structured data from PDFs and Word documents using large language models — no templates, no per-format setup. Define the fields you need, point it at your documents, choose your LLM, and ship in an afternoon. Multi-row line items, PDF annotations as few-shot examples, project chat for cross-document Q&A, and a feedback loop that improves accuracy over time. Used by logistics, manufacturing, and financial-services teams to replace manual data entry at scale.Starting Price: $0 -
37
Healnet
Healx
Rare diseases are often not well studied and there is a limited understanding of many of the aspects necessary to support a drug discovery program. Our AI platform, Healnet, overcomes these challenges by analyzing millions of drug and disease data points to find novel connections that could be turned into new treatment opportunities. By applying frontier technologies across the discovery and development pipeline, we can run multiple stages in parallel and at scale. One disease, one target, one drug: it's an overly simple model, yet it's the one used by nearly all pharmaceutical companies. The next generation of drug discovery is AI-powered, parallel and hypothesis-free. Bringing together the key three drug discovery paradigms. -
38
ERNIE 3.0 Titan
Baidu
Pre-trained language models have achieved state-of-the-art results in various Natural Language Processing (NLP) tasks. GPT-3 has shown that scaling up pre-trained language models can further exploit their enormous potential. A unified framework named ERNIE 3.0 was recently proposed for pre-training large-scale knowledge enhanced models and trained a model with 10 billion parameters. ERNIE 3.0 outperformed the state-of-the-art models on various NLP tasks. In order to explore the performance of scaling up ERNIE 3.0, we train a hundred-billion-parameter model called ERNIE 3.0 Titan with up to 260 billion parameters on the PaddlePaddle platform. Furthermore, We design a self-supervised adversarial loss and a controllable language modeling loss to make ERNIE 3.0 Titan generate credible and controllable texts. -
39
GenFlow 2.0
Baidu
GenFlow 2.0 is a next-generation AI agent system powered by Baidu Wenku’s proprietary Multi-Agent Parallel Architecture, orchestrating over 100 AI agents in parallel to reduce complex task processing from hours to under three minutes. It offers full transparency and user control throughout execution. Users can pause tasks at any stage, modify instructions on the fly, and edit intermediate results, ensuring human-AI collaboration remains dynamic and precise. To enhance reliability and accuracy, GenFlow 2.0 autonomously accesses vast knowledge bases, including Baidu Scholar’s 680 million peer-reviewed publications, Baidu Wenku’s 1.4 billion professional documents, and user-approved Netdisk files, leveraging retrieval-augmented generation and multi-agent cross-validation to minimize hallucinations. The platform supports a wide array of multimodal outputs, ranging from copywriting and visual design to slide generation, research reports, animations, and code.Starting Price: Free -
40
ScaleCloud
ScaleMatrix
Data-intensive AI, IoT and HPC workloads requiring multiple parallel processes have always run best on expensive high-end processors or accelerators, such as Graphic Processing Units (GPU). Moreover, when running compute-intensive workloads on cloud-based solutions, businesses and research organizations have had to accept tradeoffs, many of which were problematic. For example, the age of processors and other hardware in cloud environments is often incompatible with the latest applications or high energy expenditure levels that cause concerns related to environmental values. In other cases, certain aspects of cloud solutions have simply been frustrating to deal with. This has limited flexibility for customized cloud environments to support business needs or trouble finding right-size billing models or support. -
41
TigerGraph
TigerGraph
Through its Native Parallel Graph™ technology, the TigerGraph™ graph platform represents what’s next in the graph database evolution: a complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time. Combining the best ideas (MapReduce, Massively Parallel Processing, and fast data compression/decompression) with fresh development, TigerGraph delivers what you’ve been waiting for: the speed, scalability, and deep exploration/querying capability to extract more business value from your data. -
42
Qwen3-Coder
Qwen
Qwen3‑Coder is an agentic code model available in multiple sizes, led by the 480B‑parameter Mixture‑of‑Experts variant (35B active) that natively supports 256K‑token contexts (extendable to 1M) and achieves state‑of‑the‑art results comparable to Claude Sonnet 4. Pre‑training on 7.5T tokens (70 % code) and synthetic data cleaned via Qwen2.5‑Coder optimized both coding proficiency and general abilities, while post‑training employs large‑scale, execution‑driven reinforcement learning, scaling test‑case generation for diverse coding challenges, and long‑horizon RL across 20,000 parallel environments to excel on multi‑turn software‑engineering benchmarks like SWE‑Bench Verified without test‑time scaling. Alongside the model, the open source Qwen Code CLI (forked from Gemini Code) unleashes Qwen3‑Coder in agentic workflows with customized prompts, function calling protocols, and seamless integration with Node.js, OpenAI SDKs, and environment variables.Starting Price: Free -
43
In Parallel
In Parallel
The Intelligent Operating Model is more than just software; it’s a complete upgrade to your operating model that modernizes it with AI. In Parallel’s Intelligent Operating Model uses an innovative operating model framework to mirror your organization’s internal and external environments in real-time. By aligning strategy and execution continuously, this agile operating model enables your organization to proactively navigate challenges and capitalize on opportunities, driving operating model transformation and operational excellence. The Intelligent Operating Model modernizes and augments your existing operating model. Powered by advanced AI and real-time data, it reshapes how you operate, eliminating inefficiencies, reducing missed opportunities, and overcoming the roadblocks that slow you down. -
44
Aquarium
Aquarium
Aquarium's embedding technology surfaces the biggest problems in your model performance and finds the right data to solve them. Unlock the power of neural network embeddings without worrying about maintaining infrastructure or debugging embedding models. Automatically find the most critical patterns of model failures in your dataset. Understand the long tail of edge cases and triage which issues to solve first. Trawl through massive unlabeled datasets to find edge-case scenarios. Bootstrap new classes with a handful of examples using few-shot learning technology. The more data you have, the more value we offer. Aquarium reliably scales to datasets containing hundreds of millions of data points. Aquarium offers solutions engineering resources, customer success syncs, and user training to help customers get value. We also offer an anonymous mode for organizations who want to use Aquarium without exposing any sensitive data.Starting Price: $1,250 per month -
45
Baidu Qianfan
Baidu
One-stop enterprise-level large model platform, providing advanced generation AI production and application process development toolchain. Provides data labels, model training and evaluation, reasoning services, and application-integrated comprehensive functional services. Training and reasoning performance greatly improved. Perfect authentication and flow control safety mechanism, self-proclaimed content review and sensitive word filtering, multi-safety mechanism escort enterprise application. Extensive and mature practice landed, building the next generation of smart applications. Online quick test service effect, convenient smart cloud reasoning service. One-stop model customization, full process visualization operation. Large model of knowledge enhancement, unified paradigm to support multi-category downstream tasks. An advanced parallel strategy that supports large model training, compression, and deployment. -
46
Substrate
Substrate
Substrate is the platform for agentic AI. Elegant abstractions and high-performance components, optimized models, vector database, code interpreter, and model router. Substrate is the only compute engine designed to run multi-step AI workloads. Describe your task by connecting components and let Substrate run it as fast as possible. We analyze your workload as a directed acyclic graph and optimize the graph, for example, merging nodes that can be run in a batch. The Substrate inference engine automatically schedules your workflow graph with optimized parallelism, reducing the complexity of chaining multiple inference APIs. No more async programming, just connect nodes and let Substrate parallelize your workload. Our infrastructure guarantees your entire workload runs in the same cluster, often on the same machine. You won’t spend fractions of a second per task on unnecessary data roundtrips and cross-region HTTP transport.Starting Price: $30 per month -
47
KAPPA-Workstation
KAPPA
KAPPA-Workstation is an integrated engineering suite which offers analysis and modeling tools for reservoir dynamic data. Our clients told us to ‘think open and think big…’ For this reason, Generation 5 is fully 64-bit, it uses parallel processing for today’s multicore processors and data is fully integrated between KAPPA modules and other programs via OpenServer. Combining the capabilities of the new KAPPA Generation 5, Azurite offers, in an integrated environment, the ability to process raw FT data from any service company, switching seamlessly between vs time and vs depth views. QAQC, quick pretest calculation, comprehensive PTA and gradient/contact determination is available in a single workflow. Merging of vs depth and vs time data in a single application. -
48
Index by Parallel
Parallel
Index by Parallel is a new infrastructure for content in the AI era, built to show publishers, creators, writers, content owners, data providers, and AI companies what content is worth to AI agents. AI agents are already using web content to accomplish millions of tasks per day, and Index tells content owners how much they are contributing, helps them reach millions of agents instead of only human readers, and is designed to pay them when agents use their work to produce responses. Content owners can register a domain and connect content without transferring a full corpus, then Parallel’s infrastructure tracks when agents retrieve and rely on that work in real time. Index provides distribution across agentic use cases such as legal research, financial due diligence, sales intelligence, healthcare, and compliance, helping valuable content reach a new class of readers that operates at scale. -
49
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 -
50
Jurassic-2
AI21
Announcing the launch of Jurassic-2, the latest generation of AI21 Studio’s foundation models, a game-changer in the field of AI, with top-tier quality and new capabilities. And that's not all, we're also releasing our task-specific APIs, with plug-and-play reading and writing capabilities that outperform competitors. Our focus at AI21 Studio is to help developers and businesses leverage reading and writing AI to build real-world products with tangible value. Today marks two important milestones with the release of Jurassic-2 and Task-Specific APIs, empowering you to bring generative AI to production. Jurassic-2 (or J2, as we like to call it) is the next generation of our foundation models with significant improvements in quality and new capabilities including zero-shot instruction-following, reduced latency, and multi-language support. Task-specific APIs provide developers with industry-leading APIs that perform specialized reading and writing tasks out-of-the-box.Starting Price: $29 per month
