Alternatives to Galactica
Compare Galactica alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Galactica in 2026. Compare features, ratings, user reviews, pricing, and more from Galactica competitors and alternatives in order to make an informed decision for your business.
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1
Mathstral
Mistral AI
As a tribute to Archimedes, whose 2311th anniversary we’re celebrating this year, we are proud to release our first Mathstral model, a specific 7B model designed for math reasoning and scientific discovery. The model has a 32k context window published under the Apache 2.0 license. We’re contributing Mathstral to the science community to bolster efforts in advanced mathematical problems requiring complex, multi-step logical reasoning. The Mathstral release is part of our broader effort to support academic projects, it was produced in the context of our collaboration with Project Numina. Akin to Isaac Newton in his time, Mathstral stands on the shoulders of Mistral 7B and specializes in STEM subjects. It achieves state-of-the-art reasoning capacities in its size category across various industry-standard benchmarks. In particular, it achieves 56.6% on MATH and 63.47% on MMLU, with the following MMLU performance difference by subject between Mathstral 7B and Mistral 7B.Starting Price: Free -
2
Claude Opus 3
Anthropic
Opus, our most intelligent model, outperforms its peers on most of the common evaluation benchmarks for AI systems, including undergraduate level expert knowledge (MMLU), graduate level expert reasoning (GPQA), basic mathematics (GSM8K), and more. It exhibits near-human levels of comprehension and fluency on complex tasks, leading the frontier of general intelligence. All Claude 3 models show increased capabilities in analysis and forecasting, nuanced content creation, code generation, and conversing in non-English languages like Spanish, Japanese, and French.Starting Price: Free -
3
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. -
4
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. -
5
Olmo 3
Ai2
Olmo 3 is a fully open model family spanning 7 billion and 32 billion parameter variants that delivers not only high-performing base, reasoning, instruction, and reinforcement-learning models, but also exposure of the entire model flow, including raw training data, intermediate checkpoints, training code, long-context support (65,536 token window), and provenance tooling. Starting with the Dolma 3 dataset (≈9 trillion tokens) and its disciplined mix of web text, scientific PDFs, code, and long-form documents, the pre-training, mid-training, and long-context phases shape the base models, which are then post-trained via supervised fine-tuning, direct preference optimisation, and RL with verifiable rewards to yield the Think and Instruct variants. The 32 B Think model is described as the strongest fully open reasoning model to date, competitively close to closed-weight peers in math, code, and complex reasoning.Starting Price: Free -
6
Sciscoper
Sciscoper
Sciscoper is an AI powered research assistant that is used to streamline and accelerate the literature review process for STEM researchers, academics, and R&D teams. Researchers often deal with hundreds or thousands of scientific papers scattered across different sources, making it difficult to extract meaningful insights efficiently. Sciscoper solves this by using AI and natural language processing to automatically: Summarize scientific papers and research findings. Extract key insights, concepts, and relationships across documents. Generate literature reviews with citations in multiple reference styles. Organize and index papers into a structured, searchable knowledge base for easy discovery. This allows users to focus less on manual reading and note-taking, and more on analyzing results, identifying research gaps, and producing new scientific knowledge.Starting Price: $20/user/month -
7
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. -
8
Solar Pro 2
Upstage AI
Solar Pro 2 is Upstage’s latest frontier‑scale large language model, designed to power complex tasks and agent‑like workflows across domains such as finance, healthcare, and legal. Packaged in a compact 31 billion‑parameter architecture, it delivers top‑tier multilingual performance, especially in Korean, where it outperforms much larger models on benchmarks like Ko‑MMLU, Hae‑Rae, and Ko‑IFEval, while also excelling in English and Japanese. Beyond superior language understanding and generation, Solar Pro 2 offers next‑level intelligence through an advanced Reasoning Mode that significantly boosts multi‑step task accuracy on challenges ranging from general reasoning (MMLU, MMLU‑Pro, HumanEval) to complex mathematics (Math500, AIME) and software engineering (SWE‑Bench Agentless), achieving problem‑solving efficiency comparable to or exceeding that of models twice its size. Enhanced tool‑use capabilities enable the model to interact seamlessly with external APIs and data sources.Starting Price: $0.1 per 1M tokens -
9
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. -
10
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. -
11
Phi-4
Microsoft
Phi-4 is a 14B parameter state-of-the-art small language model (SLM) that excels at complex reasoning in areas such as math, in addition to conventional language processing. Phi-4 is the latest member of our Phi family of small language models and demonstrates what’s possible as we continue to probe the boundaries of SLMs. Phi-4 is currently available on Azure AI Foundry under a Microsoft Research License Agreement (MSRLA) and will be available on Hugging Face. Phi-4 outperforms comparable and larger models on math related reasoning due to advancements throughout the processes, including the use of high-quality synthetic datasets, curation of high-quality organic data, and post-training innovations. Phi-4 continues to push the frontier of size vs quality. -
12
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. -
13
Prism
OpenAI
Prism is a free, LaTeX-native scientific writing workspace designed to streamline research collaboration and publishing. It brings drafting, compiling, and collaboration into a single cloud-based environment with no local setup required. Prism integrates GPT-5.2 directly into the writing workflow, providing AI-assisted proofreading, formatting, and literature search. Researchers can collaborate with unlimited contributors in real time while viewing instant compiled previews of their work. The platform is fully project-aware, allowing AI to understand the full context of a paper, including equations, references, and revisions. Built-in LaTeX rendering, citation management, and error checking reduce time spent on manual cleanup. Prism is designed to meet scientists where they already work, making it a modern standard for scientific writing. -
14
Causaly
Causaly
Leverage the power of AI to expedite the journey from bench research and laboratory insights to the launch of life-changing therapies. Gain up to 90% in research productivity by reducing your reading time from months to minutes. Cut through the noise with a high-precision, high-accuracy search to navigate the ever-growing volume of scientific literature with ease. Save time, reduce bias and increase odds of novel discoveries. Deeply explore disease biology and conduct advanced target discovery. Causaly’s high-precision knowledge graph consolidates evidence from millions of publications, making deep, unbiased scientific exploration possible. Rapidly navigate biological cause-and-effect relationships without being an expert. Get a view of all scientific documents and uncover hidden connections. Causaly’s powerful AI machine reads millions of published biomedical literature to support better decision-making and research outcomes. -
15
Chinchilla
Google DeepMind
Chinchilla is a large language model. Chinchilla uses the same compute budget as Gopher but with 70B parameters and 4× more more data. Chinchilla uniformly and significantly outperforms Gopher (280B), GPT-3 (175B), Jurassic-1 (178B), and Megatron-Turing NLG (530B) on a large range of downstream evaluation tasks. This also means that Chinchilla uses substantially less compute for fine-tuning and inference, greatly facilitating downstream usage. As a highlight, Chinchilla reaches a state-of-the-art average accuracy of 67.5% on the MMLU benchmark, greater than a 7% improvement over Gopher. -
16
Kimi K2
Moonshot AI
Kimi K2 is a state-of-the-art open source large language model series built on a mixture-of-experts (MoE) architecture, featuring 1 trillion total parameters and 32 billion activated parameters for task-specific efficiency. Trained with the Muon optimizer on over 15.5 trillion tokens and stabilized by MuonClip’s attention-logit clamping, it delivers exceptional performance in frontier knowledge, reasoning, mathematics, coding, and general agentic workflows. Moonshot AI provides two variants, Kimi-K2-Base for research-level fine-tuning and Kimi-K2-Instruct pre-trained for immediate chat and tool-driven interactions, enabling both custom development and drop-in agentic capabilities. Benchmarks show it outperforms leading open source peers and rivals top proprietary models in coding tasks and complex task breakdowns, while its 128 K-token context length, tool-calling API compatibility, and support for industry-standard inference engines.Starting Price: Free -
17
HeyScience
HeyScience
Finding, reading, and analyzing every relevant scientific research article can quickly turn into a time-consuming, tedious task. Designed by fellow academics, our AI-powered scientific research assistant lets you focus on what you love doing most: conducting research. Stay current with an overview of what researchers in your field are working on, familiarize yourself with a specific scientist’s contributions, and assess the possibility of future collaborations. Conduct a month’s worth of literature research in a few minutes. Search and sort through millions of papers across all academic fields to find relevant knowledge in one click. Read a short, simplified summary of scientific articles and grasp key concepts and findings within minutes. Leverage our dedicated AI-reviewer for instant feedback on your manuscript prior to conference or journal submission. -
18
MiniMax M1
MiniMax
MiniMax‑M1 is a large‑scale hybrid‑attention reasoning model released by MiniMax AI under the Apache 2.0 license. It supports an unprecedented 1 million‑token context window and up to 80,000-token outputs, enabling extended reasoning across long documents. Trained using large‑scale reinforcement learning with a novel CISPO algorithm, MiniMax‑M1 completed full training on 512 H800 GPUs in about three weeks. It achieves state‑of‑the‑art performance on benchmarks in mathematics, coding, software engineering, tool usage, and long‑context understanding, matching or outperforming leading models. Two model variants are available (40K and 80K thinking budgets), with weights and deployment scripts provided via GitHub and Hugging Face. -
19
Qwen2.5-Max
Alibaba
Qwen2.5-Max is a large-scale Mixture-of-Experts (MoE) model developed by the Qwen team, pretrained on over 20 trillion tokens and further refined through Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). In evaluations, it outperforms models like DeepSeek V3 in benchmarks such as Arena-Hard, LiveBench, LiveCodeBench, and GPQA-Diamond, while also demonstrating competitive results in other assessments, including MMLU-Pro. Qwen2.5-Max is accessible via API through Alibaba Cloud and can be explored interactively on Qwen Chat.Starting Price: Free -
20
Tülu 3
Ai2
Tülu 3 is an advanced instruction-following language model developed by the Allen Institute for AI (Ai2), designed to enhance capabilities in areas such as knowledge, reasoning, mathematics, coding, and safety. Built upon the Llama 3 Base, Tülu 3 employs a comprehensive four-stage post-training process: meticulous prompt curation and synthesis, supervised fine-tuning on a diverse set of prompts and completions, preference tuning using both off- and on-policy data, and a novel reinforcement learning approach to bolster specific skills with verifiable rewards. This open-source model distinguishes itself by providing full transparency, including access to training data, code, and evaluation tools, thereby closing the performance gap between open and proprietary fine-tuning methods. Evaluations indicate that Tülu 3 outperforms other open-weight models of similar size, such as Llama 3.1-Instruct and Qwen2.5-Instruct, across various benchmarks.Starting Price: Free -
21
Edison Scientific
Edison Scientific
Edison Scientific is an AI platform designed to automate and accelerate scientific research, enabling users to move from hypothesis to validated results within a single environment. The platform integrates literature synthesis, data analysis, and molecular design workflows, allowing research teams to complete end-to-end scientific investigations at dramatically increased speed. At its core is Kosmos, an autonomous research system that performs hundreds of research tasks in parallel, transforming multimodal datasets into comprehensive reports with validated findings and publication-ready figures. Kosmos synthesizes scientific literature, public databases, and proprietary datasets, identifies novel therapeutic targets, uncovers biological mechanisms, and supports the iterative design and optimization of molecular candidates. Validated in real research settings, Kosmos has demonstrated the ability to achieve results that typically require months of human effort in a single day.Starting Price: $50 per month -
22
Llama 2
Meta
The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters. Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations. Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests. Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations. We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.Starting Price: Free -
23
NVIDIA Llama Nemotron
NVIDIA
NVIDIA Llama Nemotron is a family of advanced language models optimized for reasoning and a diverse set of agentic AI tasks. These models excel in graduate-level scientific reasoning, advanced mathematics, coding, instruction following, and tool calls. Designed for deployment across various platforms, from data centers to PCs, they offer the flexibility to toggle reasoning capabilities on or off, reducing inference costs when deep reasoning isn't required. The Llama Nemotron family includes models tailored for different deployment needs. Built upon Llama models and enhanced by NVIDIA through post-training, these models demonstrate improved accuracy, up to 20% over base models, and optimized inference speeds, achieving up to five times the performance of other leading open reasoning models. This efficiency enables handling more complex reasoning tasks, enhances decision-making capabilities, and reduces operational costs for enterprises. -
24
OpenAI o3-mini-high
OpenAI
The o3-mini-high model from OpenAI advances AI reasoning by refining deep problem-solving in coding, mathematics, and complex tasks. It features adaptive thinking time with adjustable reasoning modes (low, medium, high) to optimize performance based on task complexity. Outperforming the o1 series by 200 Elo points on Codeforces, it delivers high efficiency at a lower cost while maintaining speed and accuracy. As part of the o3 family, it pushes AI problem-solving boundaries while remaining accessible, offering a free tier and expanded limits for Plus subscribers. -
25
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. -
26
Med-PaLM 2
Google Cloud
Healthcare breakthroughs change the world and bring hope to humanity through scientific rigor, human insight, and compassion. We believe AI can contribute to this, with thoughtful collaboration between researchers, healthcare organizations, and the broader ecosystem. Today, we're sharing exciting progress on these initiatives, with the announcement of limited access to Google’s medical large language model, or LLM, called Med-PaLM 2. It will be available in the coming weeks to a select group of Google Cloud customers for limited testing, to explore use cases and share feedback as we investigate safe, responsible, and meaningful ways to use this technology. Med-PaLM 2 harnesses the power of Google’s LLMs, aligned to the medical domain to more accurately and safely answer medical questions. As a result, Med-PaLM 2 was the first LLM to perform at an “expert” test-taker level performance on the MedQA dataset of US Medical Licensing Examination (USMLE)-style questions. -
27
Opscidia
Opscidia
Opscidia is a collaborative platform that brings all the scientific and technological information. It is a scientific hub based on the latest AI technologies with multiple monitoring features to view the best scientific information in a few clicks. Scientific and technological monitoring is a time-consuming process, but essential for innovation. Opscidia has taken up the challenge of offering the best scientific information in a few clicks. Opscidia's scientific hub allows businesses to optimize monitoring time so that teams can invest more in R&D projects, client deliverables, and daily monitoring tasks. The features of the Opscidia platform include: - Identify emerging concepts - Measure scientific trends related to a product or a technology - Write scientific reports faster thanks to artificial intelligence - Collaborate and share scientific information -
28
Hippocratic AI
Hippocratic AI
Hippocratic AI is the new state of the art (SOTA) model, outperforming GPT-4 on 105 of 114 healthcare exams and certifications. Hippocratic AI has outperformed GPT-4 on 105 out of 114 tests and certifications, outperformed by a margin of five percent or more on 74 of the certifications, and outperformed by a margin of ten percent or more on 43 of the certifications. Most language models pre-train on the common crawl of the Internet, which may include incorrect and misleading information. Unlike these LLMs, Hippocratic AI is investing heavily in legally acquiring evidence-based healthcare content. We’re conducting a unique Reinforcement Learning with Human Feedback process using healthcare professionals to train and validate the model’s readiness for deployment. We call this RLHF-HP. Hippocratic AI will not release the model until a large number of these licensed professionals deem it safe. -
29
NobleAI
NobleAI
NobleAI enables companies to accelerate the development of better-performing, more environmentally sustainable, and reliably sourced chemical & material products. At NobleAI, we believe that materials science and chemistry are key to building a sustainable world and that AI is essential to unlock this potential. NobleAI’s science-based AI is a powerful fusion of novel artificial intelligence techniques and all available scientific knowledge, optimized for product development. This combination of data-driven insights and scientifically guided design delivers much higher levels of accuracy with far less data and training time. This delivers deeper insights while exhibiting greater transparency, interpretability, and scientific fidelity. -
30
OpenAI o1
OpenAI
OpenAI o1 represents a new series of AI models designed by OpenAI, focusing on enhanced reasoning capabilities. These models, including o1-preview and o1-mini, are trained using a novel reinforcement learning approach to spend more time "thinking" through problems before providing answers. This approach allows o1 to excel in complex problem-solving tasks in areas like coding, mathematics, and science, outperforming previous models like GPT-4o in certain benchmarks. The o1 series aims to tackle challenges that require deeper thought processes, marking a significant step towards AI systems that can reason more like humans, although it's still in the preview stage with ongoing improvements and evaluations. -
31
DeepSeek R2
DeepSeek
DeepSeek R2 is the anticipated successor to DeepSeek R1, a groundbreaking AI reasoning model launched in January 2025 by the Chinese AI startup DeepSeek. Building on R1’s success, which disrupted the AI industry with its cost-effective performance rivaling top-tier models like OpenAI’s o1, R2 promises a quantum leap in capabilities. It is expected to deliver exceptional speed and human-like reasoning, excelling in complex tasks such as advanced coding and high-level mathematical problem-solving. Leveraging DeepSeek’s innovative Mixture-of-Experts architecture and efficient training methods, R2 aims to outperform its predecessor while maintaining a low computational footprint, potentially expanding its reasoning abilities to languages beyond English.Starting Price: Free -
32
TradersCockpit
TradersCockpit
Looking for readymade setups backed by years of Technical Research and Backtesting. DashboardX is custom-made for your different investment and trading needs. Interested to apply the power of quantitative analysis and artificial intelligence to work for your investments and improve returns on your wealth-building corpus. Invest using SMART SIP, a scientific way known to outperform traditional SIP so as to invest more when markets are cheaper and holds back when markets appear expensive. So you sit back and relax and let the power of machine learning DRIVE your investments. All our alerts are backed with years of data. We are not biased towards any provider of financial products. We have a unique and successful methodology that integrates quantitative techniques and Technical Analysis. -
33
Mistral Large 2
Mistral AI
Mistral AI has launched the Mistral Large 2, an advanced AI model designed to excel in code generation, multilingual capabilities, and complex reasoning tasks. The model features a 128k context window, supporting dozens of languages including English, French, Spanish, and Arabic, as well as over 80 programming languages. Mistral Large 2 is tailored for high-throughput single-node inference, making it ideal for large-context applications. Its improved performance on benchmarks like MMLU and its enhanced code generation and reasoning abilities ensure accuracy and efficiency. The model also incorporates better function calling and retrieval, supporting complex business applications.Starting Price: Free -
34
LFM2
Liquid AI
LFM2 is a next-generation series of on-device foundation models built to deliver the fastest generative-AI experience across a wide range of endpoints. It employs a new hybrid architecture that achieves up to 2x faster decode and prefill performance than comparable models, and up to 3x improvements in training efficiency compared to the previous generation. These models strike an optimal balance of quality, latency, and memory for deployment on embedded systems, allowing real-time, on-device AI across smartphones, laptops, vehicles, wearables, and other endpoints, enabling millisecond inference, device resilience, and full data sovereignty. Available in three dense checkpoints (0.35 B, 0.7 B, and 1.2 B parameters), LFM2 demonstrates benchmark performance that outperforms similarly sized models in tasks such as knowledge recall, mathematics, multilingual instruction-following, and conversational dialogue evaluations. -
35
James AI
James
James AI intelligently and responsively manages your daily planning, meaning you save time, increase productivity, and complete your projects with ease. James AI saves you time, which you can either use to work even harder on your success or to dedicate yourself to other beautiful things in life. James AI adapts to your individual needs and increases your productivity in an intelligent manner, based on scientific knowledge. The artificial intelligence is constantly learning and is guided by you, not vice versa. With James AI, you will receive a daily task schedule that is perfectly matched to your needs, no more thinking about what you should do next. Just save your to-do’s and the AI will do the planning for you. James AI adapts to your individual needs and increases your productivity in an intelligent manner, based on scientific knowledge. The artificial intelligence is constantly learning and is guided by you, not vice versa.Starting Price: €4.49 -
36
Edison Analysis
Edison Scientific
Edison Analysis is a next-generation scientific data-analysis agent built by Edison Scientific. It is the analytical engine underpinning their AI Scientist platform, Kosmos, and it’s available both on Edison’s platform and via API. Edison Analysis performs complex scientific data analysis by iteratively building and updating Jupyter notebooks in a dedicated environment; given a dataset plus a prompt, the agent explores, analyzes, and interprets the data to provide comprehensive insights, reports, and visualizations, very much like a human scientist. It supports execution of Python, R, and Bash code, and includes a full suite of common scientific-analysis packages in a Docker environment. Because all work is done within a notebook, the reasoning is fully transparent and auditable; users can inspect exactly how data was manipulated, which parameters were chosen, how conclusions were drawn, and can download the notebook and associated assets at any time.Starting Price: $50 per month -
37
Scientific Study
Scientific Study
Scientific Study is your one stop shop to manage administrative tasks such as tracking teacher leave and student attendance. Use Scientific Study ERP to streamline financial tasks such as fee collection, processing salaries, transport costs and track inventory. Scientific Study is perfect for managing academic matters relating to curriculum, student performance, examinations, and CCE reports. We will create your school account based on your preferences, we will send you the user id and password on same day. We will create a school erp account on the same day of payment. Scientific Studies integrate with a wide range of applications. Scientific Study workflow functions are independent of systems, providing flexible integration options should you need to connect with multiple applications used by different subsidiaries or departments. Scientific Studies integrate with a wide range of applications. Scientific Study workflow functions are independent of systems. -
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
Nextnet
Nextnet
Do not spend your valuable time searching through different databases or worrying about different data formats or arcane queries. Instead, spend your time applying your intuition and domain expertise to discover new insights and follow the scientific leads that you think are interesting. We built Nextnet, a digital infrastructure, leveraging recent breakthroughs in natural language and explainable AI, software, graph databases, and, human-in-the-loop reinforcement learning to accelerate scientific discovery and R&D. We are building the largest, human-curated reinforcement learning data set for determining the relevance of scientific topics to each other. Use a single point of access via Sapiens’ single search box that allows you to reach out and touch upon knowledge scattered across disparate data sources. Search not only for what you know (via simple search); but discover the things you don’t know (via advanced conceptual search) using our persistent knowledge network. -
40
DeepSeek-V2
DeepSeek
DeepSeek-V2 is a state-of-the-art Mixture-of-Experts (MoE) language model introduced by DeepSeek-AI, characterized by its economical training and efficient inference capabilities. With a total of 236 billion parameters, of which only 21 billion are active per token, it supports a context length of up to 128K tokens. DeepSeek-V2 employs innovative architectures like Multi-head Latent Attention (MLA) for efficient inference by compressing the Key-Value (KV) cache and DeepSeekMoE for cost-effective training through sparse computation. This model significantly outperforms its predecessor, DeepSeek 67B, by saving 42.5% in training costs, reducing the KV cache by 93.3%, and enhancing generation throughput by 5.76 times. Pretrained on an 8.1 trillion token corpus, DeepSeek-V2 excels in language understanding, coding, and reasoning tasks, making it a top-tier performer among open-source models.Starting Price: Free -
41
Llama 4 Scout
Meta
Llama 4 Scout is a powerful 17 billion active parameter multimodal AI model that excels in both text and image processing. With an industry-leading context length of 10 million tokens, it outperforms its predecessors, including Llama 3, in tasks such as multi-document summarization and parsing large codebases. Llama 4 Scout is designed to handle complex reasoning tasks while maintaining high efficiency, making it perfect for use cases requiring long-context comprehension and image grounding. It offers cutting-edge performance in image-related tasks and is particularly well-suited for applications requiring both text and visual understanding.Starting Price: Free -
42
Mathpix
Mathpix
Mathpix is an ecosystem of products that power careers in STEM. Our tools make teaching, writing, publishing, and collaborating on scientific research easy and rewarding. Quickly convert images and PDFs to useful formats such as DOCX, LaTeX, HTML, Markdown, and more. Publish research and create assignments in half the time with cutting-edge resources. Seamlessly collaborate with colleagues, researchers, and students. Snipping Tool is a desktop app that allows you to copy math and chemistry from your screen to your clipboard with a single keyboard shortcut. Compatible with LaTeX, Markdown, and MS Word. Markdown and AI-powered collaborative editing environment for researchers with easy exporting to LaTeX, MS Word, and PDF. Convert a screenshot of an equation to LaTeX by simply pasting it into your editor. Cloud syncing all the documents across devices, autocompletion, and exporting to other formats included.Starting Price: $4.99 -
43
Ministral 8B
Mistral AI
Mistral AI has introduced two advanced models for on-device computing and edge applications, named "les Ministraux": Ministral 3B and Ministral 8B. These models excel in knowledge, commonsense reasoning, function-calling, and efficiency within the sub-10B parameter range. They support up to 128k context length and are designed for various applications, including on-device translation, offline smart assistants, local analytics, and autonomous robotics. Ministral 8B features an interleaved sliding-window attention pattern for faster and more memory-efficient inference. Both models can function as intermediaries in multi-step agentic workflows, handling tasks like input parsing, task routing, and API calls based on user intent with low latency and cost. Benchmark evaluations indicate that les Ministraux consistently outperforms comparable models across multiple tasks. As of October 16, 2024, both models are available, with Ministral 8B priced at $0.1 per million tokens.Starting Price: Free -
44
PubHive Navigator
PubHive
PubHive Navigator is an AI-powered software platform that streamlines scientific literature and safety workflows for life science companies of all sizes. It offers centralized end-to-end workflow solutions for literature review, curation, annotation, collaboration, searching, reporting, citing, and managing research. The platform features AI-powered smart workspaces for centralized literature management, collaborative research writing and team communication, reuse rights and document delivery integrations, and out-of-the-box workflows for different operation units. PubHive Navigator is designed to simplify enterprise scientific literature and safety information workflows, making it a flexible software platform for teams in drug safety and pharmacovigilance, medical affairs, clinical affairs, and R&D. -
45
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 -
46
Scientific Linux
Scientific Linux
Scientific Linux is a Fermilab sponsored project. Our primary user base is within the High Energy and High Intensity Physics community. However, our users come from a wide variety of industries with various use cases all over the globe, and sometimes off of it! Scientific Linux is a rebuild of Red Hat Enterprise Linux (property of Red Hat Inc NYSE:RHT). We informally call them “The Upstream Vendor” or “TUV”. Our references to TUV are intended to make it clear that Scientific Linux is in no way affiliated, supported, or sanctioned by upstream. By not using their name we hope to make this distinction as clear as possible. Provides a stable, scalable, and extensible operating system for scientific computing. Supports scientific research by providing methods and procedures for enabling the integration of scientific applications with the operating environment. Use the free exchange of ideas, designs, and implementations to prepare a computing platform for the next generation of computing. -
47
CoVigilAI
CoVigilAI
CoVigilAI is an AI-enabled medical literature monitoring solution that employs advanced algorithms and data analytics to proactively detect and manage adverse drug events, ensuring patient safety and regulatory compliance in real time. The platform offers streamlined tracking of scientific and medical publications across prominent global literature databases such as PubMed and Embase, with customizable search strings facilitating an effortless pharmacovigilance literature monitoring journey. Periodic surveillance of scientific and medical literature databases and publications from diverse local journals is conducted, encompassing both global literature monitoring and localized literature surveillance. Advanced algorithms categorize Individual Case Safety Reports (ICSRs) into valid, potential, and invalid cases, while automated key entity detection efficiently recognizes crucial entities like patients, medications, adverse events, and designated medical events. -
48
Claude Sonnet 3.5
Anthropic
Claude Sonnet 3.5 sets new industry benchmarks for graduate-level reasoning (GPQA), undergraduate-level knowledge (MMLU), and coding proficiency (HumanEval). It shows marked improvement in grasping nuance, humor, and complex instructions, and is exceptional at writing high-quality content with a natural, relatable tone. Claude Sonnet 3.5 operates at twice the speed of Claude Opus 3. This performance boost, combined with cost-effective pricing, makes Claude Sonnet 3.5 ideal for complex tasks such as context-sensitive customer support and orchestrating multi-step workflows.Starting Price: Free -
49
Grounded Language Model (GLM)
Contextual AI
Contextual AI introduces its Grounded Language Model (GLM), engineered specifically to minimize hallucinations and deliver highly accurate, source-based responses for retrieval-augmented generation (RAG) and agentic applications. The GLM prioritizes faithfulness to the provided data, ensuring responses are grounded in specific knowledge sources and backed by inline citations. With state-of-the-art performance on the FACTS groundedness benchmark, the GLM outperforms other foundation models in scenarios requiring high accuracy and reliability. The model is designed for enterprise use cases like customer service, finance, and engineering, where trustworthy and precise responses are critical to minimizing risks and improving decision-making. -
50
Springer
Springer
Springer is a leading global scientific, technical and medical portfolio, providing researchers in academia, scientific institutions and corporate R&D departments with quality content through innovative information, products and services. Springer has one of the strongest STM and HSS eBook collections and archives, as well as a comprehensive range of hybrid and open access journals and books under the SpringerOpen imprint. Springer is part of Springer Nature, a global publisher that serves and supports the research community. Springer Nature aims to advance discovery by publishing robust and insightful science, supporting the development of new areas of research and making ideas and knowledge accessible around the world.
