Google Cloud partners with SandboxAQ to bring specialist AI models built for scientific research

Google Cloud will sell specialist AI models built for science

Google is adding SandboxAQ's 'large quantitative models' to its cloud marketplace, pairing Gemini with AI trained on scientific equations and laboratory data. The large language models that power most of the AI industry are very good at words and surprisingly unreliable at numbers. Google's latest move is an admission that, for science, a different kind of model is needed. The company said it will start offering specialist AI models from SandboxAQ through Google Cloud, adding what SandboxAQ calls large quantitative models to the cloud marketplace. The aim is to widen enterprise and research access to AI built for drug discovery, materials science, and semiconductor manufacturing, the announcement said. The distinction is the whole point. Large language models are trained on text and excel at generating it. Large quantitative models, by SandboxAQ's description, are trained on numerical data and scientific equations rather than prose, which is meant to make them better suited to problems in chemistry, biology, and physics, fields where the right answer is a number or a structure, not a fluent paragraph. On Google Cloud, researchers will be able to combine these with Gemini, using the language model for reasoning and interface and the quantitative model for the underlying science. Google paired the marketplace move with Gemini for Science, a bundle of tools and experiments aimed at the research workflow itself. It draws on projects the company has been building for a while, including its AI co-scientist, the AlphaEvolve coding agent, an empirical research assistant, and NotebookLM, and is pitched as a way to speed up the routine, laborious steps of the scientific method rather than to replace the scientist. That framing is consistent with where Google has put its scientific weight. DeepMind's protein-structure work has already reshaped parts of drug development, and a separate effort produced an AI that found more new materials in a year than science had catalogued in its entire history. The common thread is that the highest-value AI in the sciences tends to be narrow and trained on real measurements, not general and trained on the internet. The commercial logic is straightforward. Google is competing with the other hyperscalers to be the default place enterprises run AI, and scientific and industrial R&D is a high-value segment that general chatbots do not serve well. Selling specialist models through the marketplace, the same channel through which it already offers a wide catalogue of third-party systems, lets Google capture that demand without having to build every domain model itself. It also fits a broader scramble to turn AI into actual laboratory results. DeepMind's own drug-discovery spinoff Isomorphic Labs is moving toward trials, and rivals across the industry are racing to convert algorithmic promise into treatments and materials that work outside a benchmark. Putting quantitative models in front of enterprise researchers is Google's bid to be the infrastructure underneath that race. Google said the capabilities are already in use by partners in private preview for real-world R&D, though it has been sparing with specifics on which organisations and what results. The marketplace listing is the substantive change: a category of AI that was largely confined to specialist labs becomes something a research team can rent. Whether it produces discoveries or simply faster spreadsheets is the question the private previews are meant to answer.

Google Cloud Marketplace to offer LQMs from SandboxAQ

SandboxAQ claims its LQMs can offer 'critical advances' in sectors such as life sciences, financial services and navigation. Quantum computing and AI technology company SandboxAQ is to make two of its 'large quantitative models' (LQMs) available for Google Cloud Marketplace users with the aim of driving AI-assisted developments in materials science, healthcare and drug discovery. SandboxAQ said its LQMs are "rigorous, physics-grounded scientific models" built on "real-world lab data and scientific equations" that will now interface with other AI models through Google's platform. The 'AQCat' LQM, which will be available on the storefront in Q3 of this year, "targets the most critical first step in catalyst and materials discovery, adsorption energy calculation, which is a measure of how strongly molecules bind to a catalyst surface", its maker said. Researchers will be able to use AQCat "to rapidly identify and prioritise the most promising candidates" for materials discovery "before committing costly modelling and lab resources to full evaluation", according to SandboxAQ, which said that catalysts underpin more than 90pc of all commercially produced chemical products and directly impact initiatives such as green hydrogen, sustainable aviation fuel, fertiliser production and plastics recycling. "Bringing our LQMs to Google Cloud's Marketplace will put the rigor of first-principles science directly into the hands of every researcher, in the tools they already use," said Jack D Hidary, CEO of SandboxAQ. "Pairing the reasoning of a frontier model such as Gemini with the quantitative precision of our LQMs is a powerful combination." The 'AQPotency' LQM, available later in 2026 on Google Cloud Marketplace, "will let researchers computationally identify and prioritise the most promising binders at high throughput, evaluating thousands of candidates in a fraction of the time and cost of traditional screening", according to its creator. SandboxAQ said that binding molecule identification is "the foundation of designing a safe, effective drug", and the new LQM would offer "frontier, physics-grounded drug discovery capabilities" to pharmaceutical and biotech R&D teams. Brian Goldstein, vice-president of strategic AI and independent software vendors at Google Cloud, said: "Bringing SandboxAQ's large quantitative models to [our] marketplace is one of the ways we are empowering healthcare researchers to accelerate drug discovery and solve one of the most critical gaps in healthcare today." SandboxAQ is already integrated with Anthropic's Claude AI model. It claims its LQMs can offer "critical advances" in sectors such as life sciences, financial services and navigation. The company began life at Alphabet, the parent organisation of Google, in 2016, before launching as a spin-out in 2022. SandboxAQ is chaired by Eric Schmidt, former CEO of Google. Don't miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic's digest of need-to-know sci-tech news.