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                    "Slide 1 of 4Solving frontier problems with expertsResearchers, engineers, and security specialists are pairing with Argon to push the boundaries of science, math, robotics and cyber defense.Unlocking new scientific breakthroughsArgon is helping researchers at Google and the scientific community accelerate their path to discovery and real-world impact.Accelerating roboticsArgon autonomously turns raw video to a physics-accurate simulation, estimating depth and physical boundaries, and writing the exact simulation code required to replicate those real-world environments.Scaling cybersecurity defense responsiblyArgon ties for #1 on CWE-Bench (68%) for vulnerability remediation, is our most resilient model against indirect prompt injections, and is expanding to hundreds of additional Fairwind Program partners today. Hands-on  Performance  Safety  Try Gemini 4 Argon Untangling browser feature code in ChromeQuantum chemistry open-source package optimizationOptimizing a production Python codebase in hoursMaking our open Gemma models nearly three times as fastAt Isomorphic Labs, the team is using Argon as a partner to accelerate their drug discovery and design research workflows. Argon is able to quickly synthesize complex PDFs and patents to extract pertinent information, reducing a process that typically takes weeks into hours.Ambience HealthcareAmplitudeAxiom BioBoxCartwheelDeloitteKeplerLexisNexisMinutalAQuadrillionQuoraRoboflow \u201cOn over 200 complex synthetic longitudinal charts, Gemini 4 achieved the highest recall and ICD-10 code specificity among the models we evaluated, producing concise problem lists without external lookups. That combination of medical knowledge and long-context understanding shows promise for clinician-reviewed chart workflows. We're now validating it on real patient records and excited to try it out more broadly.\u201d   \u201cArgon is doing a great job at understanding what people actually mean. Customers collect endless signals that they don't know what to do with. Argon consistently scored amongst the top in our evals for building charts that help visualize the solutions for customers. It's also meaningfully persistent about finding those kinds of needle in a haystack answers that are valuable to customers.\u201dCurtis LiuCTO, Amplitude   \u201cGemini 4 represents a step change in what AI can accomplish in real-world science. We've seen it reason through complex experimental data, from cellular imaging to mass spectrometry, and make subtle findings that traditionally require expert scientists to identify. On our Scientific Agent Benchmark, Gemini 4 was at the frontier across most tasks, including our hardest: ranking the clinical risk between two drugs.\u201dAlex CabreraFounding Engineer, Axiom Bio   \u201cGemini 4 Argon is at the frontier of enterprise knowledge work, achieving a 14% improvement in accuracy compared to Gemini 3.1 Pro. In Box\u2019s evaluation, Argon connected evidence across the full set of documents, including details embedded in figures, and carried multi-step analyses through to complete answers. This is especially valuable in data analysis and in technical fields like healthcare and life sciences, where teams need to find and interpret information across many kinds of source material.\u201dYashodha BhavnaniVP of AI Products at Box   \u201cBy integrating Gemini 4 into our 3D spatial reconstruction engine, we turn everyday video into articulated, physics-ready 3D scenes in seconds instead of hours. Across our benchmarks, Gemini outperformed every model we tested \u2014 cutting runtime nearly 100\u00d7 and token usage by 90%, unlocking physics ready and watertight 3D asset creation for our customers.\u201dAndrew CarrCo-founder and Chief Scientist, Cartwheel   \u201cEarly impressions from Gemini 4 are very strong: for long-running tasks across these workflows, it completed successfully 100% of the time in our evals, maintaining context and running through multiple tools across impressive spans. Its depth of reasoning delivers significantly higher, clearer output. Performing in-depth reasoning for domain-specific tasks without detailed prior logic or instructions is something we\u2019ve never seen with any model in its class before.\u201dGopal SrinivasanGlobal AI and Data Lead, Deloitte   \u201cOn our core financial analysis benchmarks, which span building multi-year financial statements straight from SEC filings to valuing companies with complex capital structures and announced acquisitions, Gemini 4 matched our analyst-built reference models on more than 99% of figures. Performance on our most complex workflows was at the frontier in a majority of tasks. We're excited to keep building with Gemini 4 at Kepler.\u201dGlenn LeBlancSoftware Engineer, Kepler   \u201cTo help legal professionals achieve more with Lexis+ with Prot\u00e9g\u00e9, we continuously evaluate AI models as part of the multi-model approach behind the LexisNexis Legal Intelligence Engine. In preliminary evaluations, Gemini 4 Argon demonstrated strong performance across legal knowledge, drafting, and analysis tasks, including identifying relevant citations and improving contract reviews, complaint analyses, and research memos.\u201dMin ChenChief AI Officer, LexisNexis Legal & Professional   \u201cIn early testing, Gemini 4 Argon stood out by connecting dates, documents, and financial calculations with legal precedents to develop highly substantive arguments. In one evaluation, it actually surpassed our human expert's answer key by surfacing a legally relevant detail we had missed. This demonstrates AI\u2019s potential to help professionals uncover crucial details and bring a more complete understanding to complex cases.\u201dCaio PeronaCEO, MinutalA   \u201cIn Qualia, our autonomous AI researcher, Gemini 4 Argon has been a standout in our evaluations for both capability and efficiency. On our internal benchmarks of complex, multi-step research tasks, it performs at the frontier while completing our evals 1.5x faster than peer models at a quarter of the cost per task. It excelled at coming up with novel ideas and identifying non-obvious insights about the problem, helping it maintain a clear research vision over long horizons, something today's models struggle with.\u201dTrenton ChangChief Scientist, Quadrillion   \u201cGemini 4 impressed us with the quality of its responses in our early evaluations. On Poe, people are increasingly using AI to build things, and Gemini 4 gives creators a powerful foundation for turning an idea into a tool they can refine and share.\u201dGareth JonesHead of Product, Quora   \u201cArgon ranked first in our object detection evaluations and led our new text benchmark, which uses real-world images from manufacturing, logistics, and aerial imagery. We\u2019ve fully integrated Argon into Roboflow so developers and enterprises can leverage its high precision detection and text extraction to inspect products, track inventory, and guide machines.\u201dBrad DwyerCo-founder and CTO of Roboflow  To demonstrate these capabilities in action, we tested Argon\u2019s ability to learn an out of distribution physical skill simply by watching. In an internal test, Argon watched a raw video of a human playing cornhole, mapped the spatial coordinates of the environment, and calculated the required whole-body joint movements. It then autonomously built the simulation code. When transferred onto Apptronik\u2019s Apollo humanoid, the robot quickly sank seven consecutive shots in a real-world trial.  Wiz is already using Argon for its \u201cScan for Good\u201d initiative, which protects critical public infrastructure for free. Having had early access to the model, Wiz used Argon to protect critical healthcare infrastructure. The model went beyond just spotting a vulnerability - it proactively safeguarded hundreds of thousands of patient records.  Uninterrupted frontier math and science derivationsWith 1M output tokens, Argon has the headroom to finish 100K+ token reasoning trajectories and output exhaustive, step-by-step mathematical proofs, quantum error-correction decoders, and complete computational physics solvers in one go.Full-repository generation and refactoringGenerate entire multi-file applications, scaffold complete microservices, or refactor sprawling codebases in a single pass without stitching together truncated responses.Massive legacy translationsTranslate monolithic legacy files and complex database schemas end-to-end while preserving cross-file dependencies.Exhaustive structured synthesisProduce comprehensive compliance audits, full-scale technical specifications, and massive structured datasets in a single turn.CategoryBenchmarkNotesGemini 4 ArgonGPT-6 AstraClaude Fable 5.1Claude Opus 5.5Knowledge workVals Index68.9%63.1%65.8%67.0%AutomationBenchScore51.3%41.4%31.4%42.5%Vals Finance Agent v265.4%53.5%58.9%58.6%Harvey's Legal Agent Benchmark19.6%5.4%6.7%3.8%Agentic codingDeepSWE v1.177.9%74.1%67.4%74.2%FrontierSWE v255.0%65.5%56.3%62.3%Vibe Code Bench91.9%89.6%90.3%90.3%Terminal-bench 4.057.4%58.2%57.9%66.4%ML engineeringPostTrainBench45.3%44.3%40.2%49.3%Science and mathTerminal-Bench Science 0.157.6%68.1%52.6%63.3%LABBench 288.8%85.4%68.6%73.1%RiemannBench76.0%72.0%65.6%69.6%Long contextGraphWalksUp to 128k, BFS (F1)99.7%98.7%91.4%90.6%256k to 1M, BFS (F1)84.2%71.8%65.0%66.8%Computer useAgent's Last ExamPass rate39.5%34.2%\u201438.2%OSWorld-2.0Offline subsetPartial score69.2%72.6%\u2014\u2014Multimodal understandingChartography71.6%71.0%46.2%66.3%LVBench91.7%87.5%79.7%83.7%CybersecurityCWE-bench v168.0%68.0%58.0%67.0%  Defending against misuseArgon is designed to refuse harmful requests while preserving legitimate, dual-use scientific research, as per our Frontier Safety Framework.Defending against prompt injection attacksArgon is our most resilient model yet against indirect prompt injections.Monitoring for misalignmentWe are deploying misalignment mitigations that monitor Argon\u2019s chain-of-thought and actions and stop execution when necessary.Hardening systemsWe are hardening our sandboxed environments by isolating and sealing them before high-risk training or evaluations begin.Built with ArgonGemini 4 Argon is available today for Google AI Pro and Ultra subscribersOur flagship subscription tier, giving power users, developers, and creators highest access to advanced features and capabilities across Google to accelerate their workflows.Apply for research and security programsAcademic and independent scientists can apply to get the highest usage tier in Google Antigravity free of charge for 6 months (subject to eligibility, capacity, and selection) and cybersecurity defenders can apply to join the Fairwind Program.GeminiSupercharge your creativity and productivity\u2028AI ModeAsk whatever's on your mind to get an AI powered responseGoogle AntigravityOur agent-first development platform that allows anyone to be a builderGoogle AI StudioThe fastest path from prompt to productionGemini APIGet started building with cutting-edge models\u2028Gemini platformBuild, deploy, and govern enterprise-ready agents and appsAndroid StudioThe official IDE for Android app developmentSlide 1 of 4Gemini OmniCreate anything from anything, starting with videoNano BananaCreate and edit images with GeminiGemini AudioPush new frontiers with intuitive inputs, natural expressiveness, and the ability to take actionGemini RoboticsThe intelligence layer to power any kind of robotGemini OmniCreate anything from anything, starting with videoNano BananaCreate and edit images with GeminiGemini AudioPush new frontiers with intuitive inputs, natural expressiveness, and the ability to take actionGemini RoboticsThe intelligence layer to power any kind of robot"
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Hands-on  Performance  Safety  Try Gemini 4 Argon Untangling browser feature code in ChromeQuantum chemistry open-source package optimizationOptimizing a production Python codebase in hoursMaking our open Gemma models nearly three times as fastAt Isomorphic Labs, the team is using Argon as a partner to accelerate their drug discovery and design research workflows. Argon is able to quickly synthesize complex PDFs and patents to extract pertinent information, reducing a process that typically takes weeks into hours.Ambience HealthcareAmplitudeAxiom BioBoxCartwheelDeloitteKeplerLexisNexisMinutalAQuadrillionQuoraRoboflow \u201cOn over 200 complex synthetic longitudinal charts, Gemini 4 achieved the highest recall and ICD-10 code specificity among the models we evaluated, producing concise problem lists without external lookups. That combination of medical knowledge and long-context understanding shows promise for clinician-reviewed chart workflows. We're now validating it on real patient records and excited to try it out more broadly.\u201d   \u201cArgon is doing a great job at understanding what people actually mean. Customers collect endless signals that they don't know what to do with. Argon consistently scored amongst the top in our evals for building charts that help visualize the solutions for customers. It's also meaningfully persistent about finding those kinds of needle in a haystack answers that are valuable to customers.\u201dCurtis LiuCTO, Amplitude   \u201cGemini 4 represents a step change in what AI can accomplish in real-world science. We've seen it reason through complex experimental data, from cellular imaging to mass spectrometry, and make subtle findings that traditionally require expert scientists to identify. On our Scientific Agent Benchmark, Gemini 4 was at the frontier across most tasks, including our hardest: ranking the clinical risk between two drugs.\u201dAlex CabreraFounding Engineer, Axiom Bio   \u201cGemini 4 Argon is at the frontier of enterprise knowledge work, achieving a 14% improvement in accuracy compared to Gemini 3.1 Pro. In Box\u2019s evaluation, Argon connected evidence across the full set of documents, including details embedded in figures, and carried multi-step analyses through to complete answers. This is especially valuable in data analysis and in technical fields like healthcare and life sciences, where teams need to find and interpret information across many kinds of source material.\u201dYashodha BhavnaniVP of AI Products at Box   \u201cBy integrating Gemini 4 into our 3D spatial reconstruction engine, we turn everyday video into articulated, physics-ready 3D scenes in seconds instead of hours. Across our benchmarks, Gemini outperformed every model we tested \u2014 cutting runtime nearly 100\u00d7 and token usage by 90%, unlocking physics ready and watertight 3D asset creation for our customers.\u201dAndrew CarrCo-founder and Chief Scientist, Cartwheel   \u201cEarly impressions from Gemini 4 are very strong: for long-running tasks across these workflows, it completed successfully 100% of the time in our evals, maintaining context and running through multiple tools across impressive spans. Its depth of reasoning delivers significantly higher, clearer output. Performing in-depth reasoning for domain-specific tasks without detailed prior logic or instructions is something we\u2019ve never seen with any model in its class before.\u201dGopal SrinivasanGlobal AI and Data Lead, Deloitte   \u201cOn our core financial analysis benchmarks, which span building multi-year financial statements straight from SEC filings to valuing companies with complex capital structures and announced acquisitions, Gemini 4 matched our analyst-built reference models on more than 99% of figures. Performance on our most complex workflows was at the frontier in a majority of tasks. We're excited to keep building with Gemini 4 at Kepler.\u201dGlenn LeBlancSoftware Engineer, Kepler   \u201cTo help legal professionals achieve more with Lexis+ with Prot\u00e9g\u00e9, we continuously evaluate AI models as part of the multi-model approach behind the LexisNexis Legal Intelligence Engine. In preliminary evaluations, Gemini 4 Argon demonstrated strong performance across legal knowledge, drafting, and analysis tasks, including identifying relevant citations and improving contract reviews, complaint analyses, and research memos.\u201dMin ChenChief AI Officer, LexisNexis Legal & Professional   \u201cIn early testing, Gemini 4 Argon stood out by connecting dates, documents, and financial calculations with legal precedents to develop highly substantive arguments. In one evaluation, it actually surpassed our human expert's answer key by surfacing a legally relevant detail we had missed. This demonstrates AI\u2019s potential to help professionals uncover crucial details and bring a more complete understanding to complex cases.\u201dCaio PeronaCEO, MinutalA   \u201cIn Qualia, our autonomous AI researcher, Gemini 4 Argon has been a standout in our evaluations for both capability and efficiency. 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We\u2019ve fully integrated Argon into Roboflow so developers and enterprises can leverage its high precision detection and text extraction to inspect products, track inventory, and guide machines.\u201dBrad DwyerCo-founder and CTO of Roboflow  To demonstrate these capabilities in action, we tested Argon\u2019s ability to learn an out of distribution physical skill simply by watching. In an internal test, Argon watched a raw video of a human playing cornhole, mapped the spatial coordinates of the environment, and calculated the required whole-body joint movements. It then autonomously built the simulation code. When transferred onto Apptronik\u2019s Apollo humanoid, the robot quickly sank seven consecutive shots in a real-world trial.  Wiz is already using Argon for its \u201cScan for Good\u201d initiative, which protects critical public infrastructure for free. Having had early access to the model, Wiz used Argon to protect critical healthcare infrastructure. 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