What is Gemini 3.1 Pro?
Gemini 3.1 Pro is Google’s latest advancement in the Gemini 3 model series, engineered to tackle complex tasks that demand deeper reasoning and analytical rigor. As the upgraded core intelligence behind recent breakthroughs like Gemini 3 Deep Think, it strengthens the foundation for advanced applications across science, engineering, business, and creative work. The model achieved a verified score of 77.1% on ARC-AGI-2, a benchmark designed to test novel logic problem-solving, more than doubling the reasoning performance of its predecessor, Gemini 3 Pro. This improvement reflects its ability to approach unfamiliar challenges with structured thinking rather than surface-level responses. Gemini 3.1 Pro is designed for tasks where simple outputs are not enough, enabling detailed synthesis, data consolidation, and strategic planning. It also supports creative and technical workflows, such as generating clean, production-ready animated SVG graphics directly from text prompts. Because these graphics are generated as pure code rather than pixel-based media, they remain lightweight, scalable, and web-optimized. Developers can access Gemini 3.1 Pro in preview through the Gemini API, Google AI Studio, Gemini CLI, Antigravity, and Android Studio. Enterprise users can integrate it via Gemini Enterprise Agent Platform and Gemini Enterprise for large-scale deployment. Consumers gain access through the Gemini app and NotebookLM, with expanded limits for Google AI Pro and Ultra subscribers. The preview release allows Google to gather feedback and further refine agentic workflows before broader availability. Overall, Gemini 3.1 Pro establishes a stronger baseline for intelligent, real-world problem solving across consumer, developer, and enterprise environments.
Similar Software to Gemini 3.1 Pro
Google Workspace is Google’s cloud-based productivity and collaboration suite designed to help businesses, teams, and organizations communicate, collaborate, manage data, and automate workflows through integrated applications and AI-powered tools. The platform combines premium business versions of Gmail, Google Drive, Google Meet, Calendar, Docs, Sheets, Slides, Chat, Keep, Forms, Sites, Tasks, NotebookLM, AppSheet, and Gemini AI into a unified cloud ecosystem optimized for modern workplaces. Google Workspace enables organizations to manage professional email communication, real-time document collaboration, cloud storage, video conferencing, project coordination, and business productivity from any device while maintaining centralized administration and security controls. The platform’s built-in Gemini AI capabilities provide intelligent assistance across applications, helping users draft emails, summarize meetings, generate reports, create content, analyze data, brainstorm ideas, and automate workflows using contextual information from business operations. Google Workspace also includes advanced collaboration tools such as appointment scheduling, eSignature support, AI-generated meeting notes, mail merge functionality, shared cloud storage, and real-time co-authoring for teams working across distributed environments. Security and compliance are major components of the platform, with enterprise-grade features including AI-powered data classification, endpoint management, secure access controls, S/MIME encryption, Data Loss Prevention, eDiscovery, Vault archiving, compliance management, and AI-driven threat protection. Businesses can choose from multiple subscription plans that scale from small startups to large enterprises, with options for expanded storage, advanced security controls, large video meetings, and enterprise-grade administration features.
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Gemini platform is an enterprise artificial intelligence development and machine learning platform from Google Cloud that provides the tools and infrastructure required to build, customize, deploy, and govern AI models and autonomous agents. The platform represents the evolution of Vertex AI and combines generative AI development, predictive machine learning, agent orchestration, model training, and enterprise governance within a unified environment. Its Model Garden provides access to more than 200 foundation models, including Google's Gemini family, third-party language models, and open-source alternatives that can be evaluated, customized, and deployed for different applications. Agent Studio provides a low-code workspace for designing AI agents, experimenting with prompts, testing model behavior, and prototyping intelligent applications through visual development tools. The Agent Development Kit offers a model-agnostic framework for building sophisticated agents capable of reasoning, using external tools, coordinating specialized subagents, and executing multistep workflows. Google Antigravity extends the platform's agentic capabilities with a development environment for managing AI coding agents, generating application code, and coordinating automated software engineering tasks. Gemini platform also provides custom machine learning training with support for different frameworks, configurable training jobs, hyperparameter optimization, and deployment of trained models for online or batch predictions. Its MLOps capabilities include automated pipelines, model evaluation, Model Registry, Feature Store, and monitoring tools that help engineering teams manage the machine learning lifecycle and identify performance degradation.
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GPT-6.1 Sol
GPT-6.1 Sol is OpenAI's upgraded Sol model for developers and professionals who need advanced reasoning and agentic capabilities without the higher cost of GPT-6 Astra. It is designed for coding, professional knowledge work, computer use, scientific research, factual question answering, and multi-step business workflows. OpenAI describes GPT-6.1 Sol as approaching GPT-6 Astra's intelligence across several important workloads while charging one-fifth of Astra's standard input and output token prices. On DeepSWE v1.1, which evaluates long-horizon software engineering in real codebases, GPT-6.1 Sol matches GPT-6 Astra at approximately one-fifth of the cost and exceeds GPT-6 Sol's best score by 6.4 percentage points. Its professional-work capabilities include understanding complex PDFs containing tables, charts, diagrams, and fine-print details across fields such as finance, healthcare, and legal work. On AutomationBench, GPT-6.1 Sol improves on GPT-6 Sol by 4.8 percentage points at the same reasoning setting and scores 2.2 points above Opus 5.5 at medium reasoning effort. Computer-use performance also advances significantly, with GPT-6.1 Sol outperforming GPT-6 Sol by seven percentage points on the OSWorld 2.0 offline set at maximum reasoning effort and coming within 2.1 points of GPT-6 Astra. For scientific research, the model can work with code and terminal tools on workflows involving data analysis, simulations, model fitting, and theorem proving, more than doubling GPT-6 Sol's Terminal-Bench Science 0.1 score at maximum effort. OpenAI also reports improved factual accuracy, including a reduction in the factual-error rate from 11.4% with GPT-6 Sol to 7.7% with GPT-6.1 Sol at low reasoning effort on its deliberately difficult factuality evaluation.
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Claude Fable 5.2
Claude Fable 5.2 is an advanced frontier AI model developed by Anthropic to support demanding technical work, autonomous software engineering, scientific research, and complex reasoning tasks. The model shares its underlying architecture with Claude Mythos 5.2 but includes additional cybersecurity and biology safeguards that allow Anthropic to provide broader access to its capabilities. Claude Fable 5.2 improves on previous generations through stronger code generation, engineering judgment, mathematical problem-solving, visual interpretation, and execution of long-running agentic workflows. Its software engineering capabilities enable AI agents to analyze large repositories, investigate bugs, implement features, optimize application performance, conduct code reviews, and complete substantial software migrations. The model can coordinate large groups of specialized subagents, delegate simpler tasks to smaller models, and maintain progress across extended development projects requiring multiple stages of planning, implementation, and verification. Anthropic demonstrated these capabilities through experimental projects involving a Python-to-Rust production migration and the creation of a prototype operating system using more than 1,000 coordinated subagents. Scientific and engineering capabilities include mathematical proof development, physics research, electronic circuit design, robotics control, and iterative experimentation using external computational tools. Claude Fable 5.2 achieved benchmark scores of 49.1% on FrontierCode 2.0, 69.9% on FrontierSWE v2, 51.4% on AutomationBench, 74.2% on Humanity's Last Exam with tools, and 73.4% on Chartography. The model supports configurable reasoning effort and produces output up to 30% faster than Fable 5.1, with an optional fast mode that increases token generation speed by up to 2.5 times.
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Company Facts
Company Name:
Google
Date Founded:
1998
Company Location:
United States
Company Website:
deepmind.google/models/gemini/
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