Best AI Models for Cursor

Claude Opus 5 is Anthropic’s new state-of-the-art Opus model for coding, knowledge work, automation, science, and everyday AI assistance. The model is designed to provide near-frontier intelligence at a lower cost than Claude Fable 5 while keeping the same base pricing as Opus 4.8. Claude Opus 5 performs strongly on software engineering benchmarks, business task automation, computer use, novel problem solving, visual generation, and scientific research tasks. Users can adjust effort settings to trade off intelligence, speed, and token usage depending on the task. The model is also better at verifying its work, iterating carefully, building test harnesses, debugging root causes, and solving multi-step engineering problems. Anthropic highlights improvements in life sciences, including structural biology, organic chemistry, bioinformatics, and protein-related tasks. Claude Opus 5 includes alignment and safety safeguards designed to support beneficial work while blocking higher-risk cybersecurity and biology misuse. It is available through Claude.ai, Claude Max, Claude Pro, Claude Code, Claude Cowork, and the Claude API under the model name claude-opus-5. By combining stronger reasoning, coding ability, scientific capability, configurable effort, Fast mode, and enterprise-ready deployment options, Claude Opus 5 gives users a powerful model for demanding daily work.

GPT-5.6 Luna is OpenAI’s fast, cost-efficient model in the GPT-5.6 lineup. The GPT-5.6 family includes Sol for flagship performance, Terra for balanced everyday work, and Luna for strong capability at the lowest listed price. Luna is designed for users who need scalable AI support for routine tasks, coding assistance, workflow automation, analysis, and production API use cases where speed and cost matter. According to the pasted preview text, Luna is priced below both Sol and Terra, making it the most affordable GPT-5.6 option for high-volume workloads. The model is included in GPT-5.6 benchmark previews across Terminal-Bench 2.1, GeneBench v1, ExploitBench, and ExploitGym, showing that it is part of the same technical family used for coding, biology, and cybersecurity evaluations. Luna benefits from safeguards developed across the GPT-5.6 series, including model-level refusal training, real-time cyber and biology misuse classifiers, account-level signals, differentiated access, monitoring, enforcement, and ongoing testing. These controls are designed to preserve legitimate use cases such as debugging, code review, defensive testing, security education, and productivity automation while constraining prohibited misuse. GPT-5.6 Luna is planned for broader access through ChatGPT, Codex, and the API after the limited preview period. GPT-5.6 Luna helps developers and organizations run useful AI workflows with a practical balance of affordability, responsiveness, and safety.

GPT-5.6 Sol is OpenAI’s flagship model in the GPT-5.6 series, built for high-end reasoning, coding, scientific analysis, cybersecurity, and agentic automation. The model is designed to handle complex tasks that require planning, iteration, tool coordination, long-horizon reasoning, and careful execution across multiple steps. GPT-5.6 Sol introduces max reasoning effort, giving the model more time to reason deeply through difficult problems. It also introduces ultra mode, which uses subagents to accelerate complex work and extend capability beyond a single-agent workflow. For coding, GPT-5.6 Sol is positioned for command-line workflows, software engineering tasks, debugging, testing, and multi-step tool use. In biology and quantitative research workflows, the model is designed to support genomics analysis and other long-context scientific tasks while using tokens more efficiently than prior models. For cybersecurity, GPT-5.6 Sol supports legitimate defensive work such as vulnerability research, code review, patch development, security education, and defensive testing. The model includes a layered safeguard stack with trained refusals, real-time cyber and biology misuse classifiers, account-level monitoring, differentiated access, human-in-the-loop review, and ongoing red-team testing. GPT-5.6 Sol helps trusted users and organizations access more powerful AI for technical work while maintaining stronger controls around misuse, sensitive requests, and high-risk activity.

Claude Mythos 5 is a frontier AI model from Anthropic created for highly trusted users working on advanced cybersecurity, infrastructure protection, and scientific research. It is based on the same core model as Claude Fable 5, but certain safeguards are lifted for approved partners operating under restricted access programs. The model offers exceptional performance across software engineering, cybersecurity analysis, autonomous development workflows, scientific reasoning, visual understanding, and long-context tasks. In cybersecurity, Claude Mythos 5 is positioned for cyberdefenders and critical infrastructure providers who need advanced AI support for securing complex systems. In life sciences, the model has demonstrated strong capabilities in drug design, protein research, molecular biology, and genomics. Claude Mythos 5 can perform long-running research and technical workflows with minimal high-level human input. Anthropic designed the model for controlled deployment because its advanced capabilities could create misuse risks if broadly available without safeguards. Access is initially limited to Project Glasswing partners, with broader trusted access programs planned for cybersecurity and select biology researchers. Claude Mythos 5 helps approved organizations apply powerful AI to high-impact technical and scientific challenges while operating within a stricter governance model.

Grok 4.5 is SpaceXAI’s smartest model, designed to excel at coding, agentic workflows, engineering tasks, and knowledge work. The model was trained on large-scale datasets covering coding, science, engineering, and math, with additional reinforcement learning focused on multi-step software engineering. It is built to perform well on real engineering workflows, including debugging, terminal-based tasks, complex code generation, Rust and C/C++ development, and app building from minimal prompts. Grok 4.5 is served at fast-model speeds while using fewer output tokens on comparable coding tasks, helping teams complete technical work more quickly and cost-effectively. The model is also available in Grok Build, where it can help create Excel models, PowerPoint presentations, Word documents, diagrams, business review decks, and research-supported productivity assets. Developers can access Grok 4.5 through the SpaceXAI API, Cursor, and Grok Build, with simple API key setup and support for direct integration into coding and automation workflows. Its pricing is positioned for high-intelligence work at scale, with per-million-token rates for both input and output usage. Grok 4.5 is also trained for agentic execution, allowing it to handle longer technical rollouts and multi-step problem solving more effectively. For developers, engineering teams, and knowledge workers, Grok 4.5 provides a powerful AI model for software creation, office automation, technical reasoning, and production-grade agent workflows.

Gemini 3.6 Flash is Google’s workhorse Flash model for developers and enterprises building production AI agents at scale. The model is designed to deliver higher quality than Gemini 3.5 Flash while improving token efficiency, latency, and overall task cost. Google says Gemini 3.6 Flash uses 17% fewer output tokens than 3.5 Flash on the Artificial Analysis Index and can show even larger efficiency gains on certain software engineering benchmarks. It is priced lower than 3.5 Flash at $1.50 per 1 million input tokens and $7.50 per 1 million output tokens. Gemini 3.6 Flash improves performance in coding, ML research, computer use, knowledge work, document parsing, chart analysis, report drafting, and data-heavy workflows. The model also supports built-in computer use through the Gemini API and Gemini Enterprise, making it more useful for agentic systems that need to operate across digital environments. Google highlights customer use cases involving financial transcript analysis, code migrations, visual workflows, and interactive design tools. The model includes enhanced Frontier Safety safeguards for CBRN and cyber offense misuse while aiming to reduce unnecessary refusals for beneficial uses. By combining efficiency, stronger reasoning, multimodal ability, computer use, and enterprise availability, Gemini 3.6 Flash gives teams a practical model for scaling AI agents in production.

GPT-5.6 Terra is OpenAI’s balanced GPT-5.6 model for users who need strong performance across everyday work, development tasks, enterprise workflows, and technical analysis. The model is part of the GPT-5.6 family alongside Sol and Luna, with Terra positioned as the middle tier for capable, cost-efficient use. Terra is described as having competitive performance to GPT-5.5 while being 2x cheaper, making it useful for teams that want advanced capability without always using the flagship model. It supports coding workflows, agentic tasks, cybersecurity-related defensive work, biology workflows, knowledge work, and tool-assisted automation. In benchmark previews, Terra appears alongside Sol and Luna in evaluations for coding, biology, ExploitBench, and ExploitGym. The model benefits from the GPT-5.6 safeguard stack, which includes model-level refusals for prohibited cyber assistance, real-time cyber and biology misuse classifiers, and account-level risk review. These safeguards are designed to preserve access to legitimate work such as code review, debugging, vulnerability research, patch development, security education, and defensive testing. GPT-5.6 Terra is planned for availability through the API, Codex, and broader OpenAI products after the limited preview period. GPT-5.6 Terra helps teams get a balanced model for high-quality AI work when they need strong reasoning and automation at a lower cost than Sol.

Gemini 3.5 Pro is Google’s expected flagship Pro model for the Gemini 3.5 generation, built for users who need advanced intelligence across reasoning, coding, multimodal analysis, and agentic execution. The model is positioned as a higher-capability option for complex work that requires stronger planning, deeper instruction following, and more reliable handling of multi-step tasks. It is expected to serve demanding use cases such as software engineering, research synthesis, data analysis, enterprise automation, AI agents, and advanced productivity workflows. Gemini 3.5 Pro will likely expand on the Gemini 3 model family’s focus on state-of-the-art reasoning, tool use, and multimodal understanding. Unlike Flash models, which prioritize speed and cost efficiency, Gemini 3.5 Pro is expected to prioritize maximum capability for more difficult and high-value tasks. Developers may use it to build coding assistants, autonomous agents, technical copilots, business analysis tools, and applications that need to process complex context. Its anticipated strengths include long-horizon task execution, advanced code generation, structured problem solving, and improved performance on workflows that require careful reasoning. Gemini 3.5 Pro is not yet broadly documented as a generally available model, so businesses should treat it as an upcoming release rather than a fully launched product. Once available, it is expected to become a strong option for teams that want Google’s most capable Gemini 3.5 model for serious AI application development.

GLM-5.2 is a next-generation large language model built for users who need strong reasoning, coding support, and agentic AI capabilities. It can assist with complex software development tasks, technical problem-solving, automation workflows, and advanced research projects. The model is designed to process long-context information, which makes it helpful for analyzing large documents, reviewing codebases, and maintaining continuity across multi-step tasks. GLM-5.2 supports developers and organizations that want to create AI-powered tools capable of planning, reasoning, and executing more sophisticated workflows. Its architecture is structured to deliver high performance while improving efficiency for demanding AI use cases. Businesses can use GLM-5.2 to enhance productivity, streamline engineering processes, and build more capable intelligent applications. It is also useful for teams that need AI assistance across documentation, data interpretation, coding, testing, and workflow automation. The model’s emphasis on agentic engineering makes it well-suited for applications that require more than simple text generation. GLM-5.2 provides a flexible AI foundation for companies looking to bring advanced reasoning and automation into their products or internal operations.

Claude Fable 5 is Anthropic’s most capable generally available AI model, built to tackle demanding tasks across software development, research, business analysis, scientific exploration, and enterprise productivity. The model demonstrates state-of-the-art performance in coding, reasoning, visual understanding, long-context processing, and autonomous task execution. Claude Fable 5 can analyze large codebases, interpret complex documents and datasets, generate detailed reports, and assist with advanced decision-making processes. Its enhanced memory capabilities allow it to remain effective during long-running workflows and multi-step projects. The model also delivers strong performance in image analysis, chart interpretation, scientific reasoning, and technical problem-solving. Anthropic has incorporated advanced safety classifiers that detect certain high-risk topics and automatically redirect those interactions to a more restricted model experience. These safeguards are designed to reduce misuse while still providing productive assistance for legitimate users. Claude Fable 5 is available through the Claude platform and API, enabling developers and organizations to integrate advanced AI capabilities into their applications and workflows. The platform is designed to help businesses improve productivity, accelerate innovation, and streamline complex knowledge work.

GPT-5.5 is a next-generation AI system built for execution-heavy workflows across coding, research, business analysis, and scientific tasks. It can interpret complex instructions, break them into actionable steps, and carry them through to completion while interacting with tools and systems. The model supports creating applications, generating reports, analyzing datasets, and navigating software environments seamlessly. It also integrates with workspace agents—custom AI agents that automate recurring and multi-step processes across teams. These agents can handle tasks such as lead research, reporting, and workflow automation, either on demand or on schedules. GPT-5.5 enhances productivity by reducing manual effort and enabling continuous task execution across tools. With enterprise-grade safeguards and monitoring, it ensures secure and controlled automation. It is well-suited for organizations looking to scale operations and improve efficiency through AI-driven workflows.

Cursor has introduced Composer 2.5, a next-generation AI coding assistant built to deliver stronger reasoning, better collaboration, and improved reliability during software development tasks. The upgraded model performs better on long-running coding workflows and can manage complicated instructions with greater consistency than earlier Composer versions. Cursor expanded the training process by scaling compute resources, generating more advanced reinforcement learning environments, and refining behavioral traits that improve the developer experience. One of the key innovations in Composer 2.5 is its targeted textual feedback system, which helps the model learn from localized mistakes inside long coding trajectories instead of relying only on broad reward signals. This training method allows the AI to improve coding style, communication quality, and tool usage accuracy in a more focused way. The company also increased the amount of synthetic coding data by 25 times compared to Composer 2, giving the model exposure to more difficult and realistic programming tasks. During development, the system demonstrated sophisticated reasoning abilities by uncovering hidden implementation details and reverse-engineering deleted functionality inside synthetic environments. Composer 2.5 additionally uses advanced distributed training methods such as Sharded Muon and dual mesh HSDP to optimize large-scale model training performance. Available directly inside Cursor, the model comes in both standard and fast variants with different pricing tiers designed for developers, teams, and enterprise-scale engineering workflows.

Gemini 3.5 Flash Cyber is a dedicated model designed specifically for cybersecurity, built upon Gemini 3.5 Flash, and refined to efficiently discover, validate, and resolve vulnerabilities at scale. Its primary objective is to support defensive security operations by enabling organizations to quickly pinpoint critical vulnerabilities and produce dependable patches before they can be exploited. The remarkable blend of performance and efficiency offered by Flash provides an excellent basis for code scanning, assessing security issues, confirming the authenticity of findings, and suggesting precise remediation strategies within extensive software environments. In the CodeMender framework, numerous Gemini 3.5 Flash Cyber agents collaborate seamlessly, merging their insights into a comprehensive report that enhances the system's ability to analyze vulnerabilities from various perspectives and elevate the overall quality of the findings. This collaborative agent framework ensures exceptional performance on CyberGym, which serves as a benchmark for assessing cybersecurity effectiveness, while also fostering continuous improvement in vulnerability management practices. Ultimately, the capabilities of Gemini 3.5 Flash Cyber not only streamline security workflows but also strengthen an organization's resilience against potential threats.

Gemini 3.5 Flash is Google’s high-performance multimodal AI model built to deliver frontier-level intelligence, fast execution speeds, and advanced agentic capabilities for coding, automation, and enterprise workflows. As the first release in the Gemini 3.5 series, the model is designed to help developers, businesses, and users execute complex long-horizon tasks through AI-powered reasoning, workflow orchestration, and intelligent automation. Gemini 3.5 Flash combines powerful coding performance, multimodal understanding, and real-time responsiveness while outperforming earlier Gemini models and competing frontier AI systems across several coding and reasoning benchmarks. The model is optimized for agentic workflows, allowing it to plan, execute, and manage multi-step tasks such as software development, infrastructure management, document preparation, and business process automation through the updated Antigravity harness. Gemini 3.5 Flash can also deploy collaborative subagents that work together under supervision to complete demanding workflows more efficiently and at lower operational cost. Beyond coding and automation, the platform generates richer graphics, dynamic web interfaces, interactive animations, and advanced multimodal experiences that support developers and enterprise users building AI-driven applications. Google has integrated Gemini 3.5 Flash across the Gemini app, AI Mode in Google Search, Google AI Studio, Android Studio, Gemini Enterprise Agent Platform, and enterprise AI services to expand access to advanced AI capabilities globally. The model also powers Gemini Spark, Google’s new personal AI agent designed to operate continuously and assist users with digital life management and automated task execution.

Claude Opus 4.8 is Anthropic’s newest flagship AI model built to improve coding performance, reasoning accuracy, agentic task execution, and collaborative AI workflows for developers, enterprises, and advanced productivity use cases. The model serves as an upgrade to Claude Opus 4.7, delivering measurable improvements across benchmarks related to coding, practical reasoning, software engineering, and autonomous task management while maintaining the same pricing structure for standard usage. One of the most significant improvements in Claude Opus 4.8 is its enhanced honesty and judgment during complex tasks, reducing the likelihood of unsupported claims, hidden errors, or overlooked flaws in generated code and analytical outputs. Anthropic’s evaluations show that Opus 4.8 is substantially less likely than previous versions to allow software defects or reasoning mistakes to pass without flagging uncertainty or requesting clarification. The platform introduces new effort control settings that allow users to adjust how deeply the model reasons through tasks, balancing response quality, processing depth, speed, and token usage depending on workflow requirements. Claude Opus 4.8 also powers new dynamic workflow functionality in Claude Code, enabling the model to coordinate hundreds of parallel subagents within a single session to handle large-scale software engineering tasks such as codebase migrations and extensive automation projects. The model supports high-speed fast mode processing, now significantly more affordable than previous versions, while also offering higher-effort reasoning modes optimized for difficult coding and operational workflows.

GPT-4, or Generative Pre-trained Transformer 4, is a highly advanced unsupervised language model that is anticipated for release by OpenAI. As the successor to GPT-3, it belongs to the GPT-n series of natural language processing models and was developed using an extensive dataset comprising 45TB of text, enabling it to generate and comprehend text in a manner akin to human communication. Distinct from many conventional NLP models, GPT-4 operates without the need for additional training data tailored to specific tasks. It is capable of generating text or responding to inquiries by utilizing only the context it creates internally. Demonstrating remarkable versatility, GPT-4 can adeptly tackle a diverse array of tasks such as translation, summarization, question answering, sentiment analysis, and more, all without any dedicated task-specific training. This ability to perform such varied functions further highlights its potential impact on the field of artificial intelligence and natural language processing.

The GPT-3.5 series represents an advancement in OpenAI's large language models, building on the capabilities of its predecessor, GPT-3. These models excel at comprehending and producing human-like text, with four primary variations designed for various applications. The core GPT-3.5 models are intended to be utilized through the text completion endpoint, while additional models are optimized for different endpoint functionalities. Among these, the Davinci model family stands out as the most powerful, capable of executing any task that the other models can handle, often requiring less detailed input. For tasks that demand a deep understanding of context, such as tailoring summaries for specific audiences or generating creative content, the Davinci model tends to yield superior outcomes. However, this enhanced capability comes at a cost, as Davinci requires more computing resources, making it pricier for API usage and slower compared to its counterparts. Overall, the advancements in GPT-3.5 not only improve performance but also expand the range of potential applications.

Claude Sonnet 3.5 sets a new standard for AI performance with outstanding benchmarks in graduate-level reasoning (GPQA), undergraduate-level knowledge (MMLU), and coding proficiency (HumanEval). This model shows significant improvements in understanding nuance, humor, and complex instructions, while consistently producing high-quality content that resonates naturally with users. Operating at twice the speed of Claude Opus 3, it delivers faster and more efficient results, making it perfect for use cases such as context-sensitive customer support and multi-step workflow automation.

Claude Sonnet 3.7, a state-of-the-art AI model by Anthropic, is designed for versatility, offering users the option to switch between quick, efficient responses and deeper, more reflective answers. This dynamic model shines in complex problem-solving scenarios, where high-level reasoning and nuanced understanding are crucial. By allowing Claude to pause for self-reflection before answering, Sonnet 3.7 excels in tasks that demand deep analysis, such as coding, natural language processing, and critical thinking applications. Its flexibility makes it an invaluable tool for professionals and organizations looking for an adaptable AI that delivers both speed and thoughtful insights.

GPT-4.1 represents a significant upgrade in generative AI, with notable advancements in coding, instruction adherence, and handling long contexts. This model supports up to 1 million tokens of context, allowing it to tackle complex, multi-step tasks across various domains. GPT-4.1 outperforms earlier models in key benchmarks, particularly in coding accuracy, and is designed to streamline workflows for developers and businesses by improving task completion speed and reliability.

Gemini 3 Pro is a next-generation AI model from Google designed to push the boundaries of reasoning, creativity, and code generation. With a 1-million-token context window and deep multimodal understanding, it processes text, images, and video with unprecedented accuracy and depth. Gemini 3 Pro is purpose-built for agentic coding, performing complex, multi-step programming tasks across files and frameworks—handling refactoring, debugging, and feature implementation autonomously. It integrates seamlessly with development tools like Google Antigravity, Gemini CLI, Android Studio, and third-party IDEs including Cursor and JetBrains. In visual reasoning, it leads benchmarks such as MMMU-Pro and WebDev Arena, demonstrating world-class proficiency in image and video comprehension. The model’s vibe coding capability enables developers to build entire applications using only natural language prompts, transforming high-level ideas into functional, interactive apps. Gemini 3 Pro also features advanced spatial reasoning, powering applications in robotics, XR, and autonomous navigation. With its structured outputs, grounding with Google Search, and client-side bash tool, Gemini 3 Pro enables developers to automate workflows and build intelligent systems faster than ever.

Claude Opus 4.7 is an advanced AI model built to push the boundaries of software engineering, automation, and complex reasoning tasks. Compared to Opus 4.6, it delivers notable improvements in handling challenging coding workflows and executing long-duration tasks with consistency. The model excels at strictly following user instructions, reducing ambiguity and improving output accuracy. It also introduces stronger self-verification capabilities, allowing it to check and refine its own results before presenting them. One of its key upgrades is enhanced multimodal functionality, particularly its ability to process higher-resolution images with greater clarity. This enables more precise analysis of visuals such as technical diagrams, dense screenshots, and structured data layouts. Opus 4.7 is also more refined in generating professional content, including polished documents, presentations, and interface designs. In real-world applications, it performs effectively across domains like finance, legal analysis, and business workflows. The model incorporates improved memory features, allowing it to retain context across extended sessions and reduce repetitive input requirements. It also introduces built-in safeguards to detect and prevent misuse, especially in sensitive cybersecurity scenarios. With broad availability across APIs and cloud platforms, Opus 4.7 offers developers and enterprises a powerful, scalable AI solution.

Grok Build 0.1 is xAI’s purpose-built coding model created to support advanced software engineering and AI-driven development workflows. Unlike general-purpose language models, it focuses on agentic coding tasks where AI systems must plan, execute, and refine multiple steps to complete a project. The model can analyze both text and visual inputs, allowing it to work with source code, screenshots, technical diagrams, and project documentation. Developers can use it for activities such as debugging, code generation, refactoring, testing, and workflow automation. Grok Build 0.1 offers native support for tool calling and structured outputs, making it easier to integrate into development environments and automated systems. Its large 256K-token context window enables the model to understand extensive repositories and long development sessions without losing context. The platform is designed to work efficiently with coding agents that need to reason through problems rather than simply respond to prompts. xAI positions the model as a successor to earlier coding-focused Grok variants, with stronger support for agent-driven development processes. Grok Build 0.1 helps engineering teams accelerate software delivery while maintaining context across large and complex projects.

Claude Sonnet 4 is an advanced AI model that enhances coding, reasoning, and problem-solving capabilities, perfect for developers and businesses in need of reliable AI support. This new version of Claude Sonnet significantly improves its predecessor’s capabilities by excelling in coding tasks and delivering precise, clear reasoning. With a 72.7% score on SWE-bench, it offers exceptional performance in software development, app creation, and problem-solving. Claude Sonnet 4’s improved handling of complex instructions and reduced errors in codebase navigation make it the go-to choice for enhancing productivity in technical workflows and software projects.

xAI’s Grok 4 represents a major step forward in AI technology, delivering advanced reasoning, multimodal understanding, and improved natural language capabilities. Built on the powerful Colossus supercomputer, Grok 4 can process text and images, with video input support expected soon, enhancing its ability to interpret cultural and contextual content such as memes. It has outperformed many competitors in benchmark tests for scientific and visual reasoning, establishing itself as a top-tier model. Focused on technical users, researchers, and developers, Grok 4 is tailored to meet the demands of advanced AI applications. xAI has strengthened moderation systems to prevent inappropriate outputs and promote ethical AI use. This release signals xAI’s commitment to innovation and responsible AI deployment. Grok 4 sets a new standard in AI performance and versatility. It is poised to support cutting-edge research and complex problem-solving across various fields.