Best AI Coding Models - Page 7

Compare the Top AI Coding Models as of June 2026 - Page 7

  • 1
    GPT-5.2-Codex
    GPT-5.2-Codex is OpenAI’s most advanced agentic coding model, built for complex, real-world software engineering and defensive cybersecurity work. It is a specialized version of GPT-5.2 optimized for long-horizon coding tasks such as large refactors, migrations, and feature development. The model maintains full context over extended sessions through native context compaction. GPT-5.2-Codex delivers state-of-the-art performance on benchmarks like SWE-Bench Pro and Terminal-Bench 2.0. It operates reliably across large repositories and native Windows environments. Stronger vision capabilities allow it to interpret screenshots, diagrams, and UI designs during development. GPT-5.2-Codex is designed to be a dependable partner for professional engineering workflows.
  • 2
    Xiaomi MiMo Studio

    Xiaomi MiMo Studio

    Xiaomi Technology

    MiMo Studio is a web-based AI chat and development interface powered by Xiaomi’s MiMo models that lets users interact directly with advanced language models like MiMo-V2-Flash for real-time conversational AI, search-augmented responses, reasoning, and code generation. It acts like an interactive “AI playground” where users can chat with the model to get answers, ask for explanations, generate or debug code, and explore ideas interactively without installing software. It supports features such as web search integration and toggleable modes that switch between instant replies and deeper “thinking” responses for more complex tasks, helping developers and creators explore tasks from research to functional output. Because it’s browser-based, it provides easy online access to Xiaomi’s cutting-edge AI models, enabling experimentation with large-context reasoning, problem solving, and multi-turn interactions.
  • 3
    PlayerZero

    PlayerZero

    PlayerZero

    PlayerZero is an AI-driven predictive quality platform designed to help engineering, QA, and support teams monitor, diagnose, and resolve software issues before they impact customers by deeply understanding complex codebases and simulating how code will behave in real-world conditions. It applies proprietary AI models and semantic graph analysis to integrate signals from source code, runtime telemetry, customer tickets, documentation, and historical data, giving users unified, context-rich insights into what their software does, why it’s broken, and how to fix or improve it. Its agentic debugging agents can autonomously triage, root cause analyze, and even suggest fixes for issues, reducing escalations and accelerating resolution times while preserving audit trails, governance, and approval workflows. PlayerZero also includes CodeSim, an agentic code simulation capability powered by the Sim-1 model that predicts the impact of changes.
  • 4
    GPT-5.3-Codex
    GPT-5.3-Codex is OpenAI’s most advanced agentic coding model, designed to handle complex professional work on a computer. It combines frontier-level coding performance with advanced reasoning and real-world task execution. The model is faster than previous Codex versions and can manage long-running tasks involving research, tools, and deployment. GPT-5.3-Codex supports real-time interaction, allowing users to steer progress without losing context. It excels at software engineering, web development, and terminal-based workflows. Beyond code generation, it assists with debugging, documentation, testing, and analysis. GPT-5.3-Codex acts as an interactive collaborator rather than a single-turn coding tool.
  • 5
    Gemini 3.1 Pro
    Gemini 3.1 Pro is Google’s upgraded core intelligence model designed for complex tasks that require advanced reasoning. Building on the Gemini 3 series, it delivers significant improvements in problem-solving performance and logical pattern recognition. On the ARC-AGI-2 benchmark, Gemini 3.1 Pro achieved a verified score of 77.1%, more than doubling the reasoning performance of Gemini 3 Pro. The model is engineered for challenges where simple answers are insufficient, enabling deeper analysis, synthesis, and creative output. It can generate practical outputs such as animated, website-ready SVGs directly from text prompts, combining intelligence with real-world usability. Gemini 3.1 Pro is rolling out in preview across consumer, developer, and enterprise platforms including the Gemini app, NotebookLM, Gemini API, Gemini Enterprise Agent Platform, and Android Studio. With expanded access for Google AI Pro and Ultra users, 3.1 Pro sets a stronger baseline for agentic workflows.
  • 6
    GPT‑5.3‑Codex‑Spark
    GPT-5.3-Codex-Spark is an ultra-fast coding model designed for real-time collaboration inside Codex. Built as a smaller version of GPT-5.3-Codex, it delivers over 1000 tokens per second when served on low-latency Cerebras hardware. The model is optimized for interactive coding tasks, enabling developers to make targeted edits and see results almost instantly. With a 128k context window, Codex-Spark supports substantial project context while maintaining speed. It focuses on lightweight, precise edits and does not automatically run tests unless prompted. Infrastructure upgrades such as persistent WebSocket connections significantly reduce latency across the full request-response pipeline. Released as a research preview for ChatGPT Pro users, Codex-Spark marks the first milestone in OpenAI’s partnership with Cerebras.
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    Gemini 3.1 Flash-Lite
    Gemini 3.1 Flash-Lite is Google’s fastest and most cost-efficient model in the Gemini 3 series, designed for high-volume developer workloads. It delivers strong performance at scale while maintaining affordability, with pricing set at $0.25 per million input tokens and $1.50 per million output tokens. The model significantly improves speed, offering a 2.5x faster time to first answer token and a 45% increase in output speed compared to Gemini 2.5 Flash. Despite its lower cost tier, it achieves high benchmark results, including an Elo score of 1432 and strong performance across reasoning and multimodal evaluations. Gemini 3.1 Flash-Lite supports adaptive “thinking levels,” allowing developers to control how much reasoning power is used for different tasks. It is suitable for large-scale applications such as translation, content moderation, user interface generation, and simulation building.
  • 8
    GPT-5.3 Instant
    GPT-5.3 Instant is an updated version of ChatGPT’s most-used model, designed to make everyday conversations more fluid, helpful, and accurate. The release focuses on improving tone, relevance, and conversational flow based directly on user feedback. It reduces unnecessary refusals and cuts back on overly cautious disclaimers, delivering clearer and more direct answers when appropriate. The model also improves how it integrates web results, providing better-contextualized information rather than long lists of loosely connected links. Accuracy has been strengthened, with measurable reductions in hallucinations across both high-stakes domains and everyday queries. GPT-5.3 Instant enhances creative writing capabilities, producing more textured, emotionally resonant prose. It is available to all ChatGPT users and developers via the API under ‘gpt-5.3-chat-latest,’ with legacy versions scheduled for retirement.
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    GPT-5.4 Pro
    GPT-5.4 Pro is an advanced AI model developed by OpenAI to deliver high-performance capabilities for professional and complex tasks. It combines improvements in reasoning, coding, and agent-based workflows into a single unified system. The model is designed to work efficiently across professional tools such as spreadsheets, presentations, documents, and development environments. GPT-5.4 Pro also includes native computer-use capabilities, enabling AI agents to interact with software, websites, and operating systems to complete tasks. With support for up to one million tokens of context, it can manage long workflows and large datasets more effectively than previous models. The model also improves tool usage, allowing it to search for and select the right tools during multi-step processes. By delivering more accurate outputs with fewer tokens, GPT-5.4 Pro helps professionals complete complex work faster and more efficiently.
  • 10
    GPT-5.4 mini
    GPT-5.4 mini is a fast and efficient AI model designed for high-performance tasks such as coding, reasoning, and multimodal understanding. It delivers strong capabilities similar to larger models while maintaining lower latency and cost. The model is optimized for responsive applications where speed is critical, including coding assistants and real-time workflows. GPT-5.4 mini supports advanced features such as tool use, function calling, and image interpretation. It performs well on complex tasks while running significantly faster than previous mini models. The model is also suitable for subagent systems, where it handles smaller tasks within larger AI workflows. By combining speed, efficiency, and strong performance, GPT-5.4 mini enables scalable AI applications across various use cases.
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    GPT-5.4 nano
    GPT-5.4 nano is a lightweight and highly efficient AI model designed for fast, cost-effective task execution. It is optimized for simple and high-volume tasks such as classification, data extraction, and basic coding support. The model delivers quick responses with minimal latency, making it ideal for real-time and large-scale applications. GPT-5.4 nano improves significantly over previous nano models in both performance and efficiency. It supports essential capabilities like tool use and structured data processing. The model is commonly used as a supporting component within larger AI systems. By focusing on speed and affordability, GPT-5.4 nano enables scalable automation across various workflows.
  • 12
    Qwen3.6-Plus
    Qwen3.6-Plus is an advanced AI model developed by Alibaba Cloud, designed to power real-world intelligent agents and complex workflows. It introduces significant improvements in agentic coding, enabling developers to handle everything from frontend development to large-scale codebase management. The model features a massive 1 million token context window, allowing it to process and reason over long and complex inputs. It integrates reasoning, memory, and execution capabilities to deliver highly accurate and reliable results. Qwen3.6-Plus also enhances multimodal capabilities, enabling it to understand and analyze images, videos, and documents. The platform is optimized for real-world applications, including automation, planning, and tool-based workflows. Overall, it provides a powerful foundation for building next-generation AI agents and intelligent systems.
  • 13
    GPT-5.5 Thinking
    GPT-5.5 Thinking is an advanced AI capability from OpenAI designed to handle complex, multi-step tasks with greater intelligence and autonomy. It enables users to provide high-level instructions while the model plans, executes, and refines tasks independently. The system excels in areas such as coding, research, data analysis, and document creation. It can navigate across tools, check its own work, and adapt to ambiguous or incomplete inputs. GPT-5.5 Thinking is optimized for both speed and efficiency, delivering high-quality outputs while using fewer computational resources. It also supports long-context understanding, allowing it to process large datasets and extended workflows. Strong safeguards are built in to ensure responsible and secure usage. Overall, it represents a shift toward more autonomous, agent-like AI that can complete real-world tasks end-to-end.
  • 14
    MiMo-V2.5-Pro

    MiMo-V2.5-Pro

    Xiaomi Technology

    Xiaomi MiMo-V2.5-Pro is an advanced open-source AI model designed to handle complex, long-horizon tasks with strong agentic capabilities. It features a Mixture-of-Experts architecture with over one trillion parameters and a large context window of up to one million tokens. The model is built to perform sophisticated reasoning, coding, and problem-solving across extended workflows. It demonstrates high performance on benchmark tests related to software engineering, reasoning, and general intelligence. MiMo-V2.5-Pro can autonomously complete complex projects, such as building full software systems or optimizing engineering designs. It uses hybrid attention mechanisms to balance efficiency and performance across long contexts. The model is also optimized for token efficiency, reducing computational cost while maintaining strong results. By combining scalability, efficiency, and advanced reasoning, MiMo-V2.5-Pro represents a major step forward in open-source AI models.
  • 15
    MiMo-V2.5

    MiMo-V2.5

    Xiaomi Technology

    Xiaomi MiMo-V2.5 is an advanced open-source AI model designed to combine strong agentic capabilities with native multimodal understanding. It can process and reason across text, images, and audio within a single unified system. The model uses a sparse Mixture-of-Experts architecture with hundreds of billions of parameters for efficient performance. It supports an extended context window of up to one million tokens, enabling long and complex workflows. MiMo-V2.5 is built to handle tasks such as coding, reasoning, and multimodal analysis with high accuracy. It incorporates dedicated visual and audio encoders to enhance perception and cross-modal reasoning. The model demonstrates strong benchmark performance across coding, reasoning, and multimodal tasks. By combining multimodality, efficiency, and agentic intelligence, MiMo-V2.5 advances the capabilities of open-source AI systems.
  • 16
    SubQ

    SubQ

    Subquadratic

    SubQ is a large language model developed by Subquadratic, designed specifically for long-context reasoning tasks. It can process up to 12 million tokens in a single prompt, allowing it to analyze entire codebases, long histories, and complex datasets at once. The model uses a sub-quadratic sparse-attention architecture that improves efficiency by focusing only on the most relevant relationships in the data. This approach reduces computational overhead while maintaining strong performance on large-scale tasks. SubQ is optimized for use cases such as software engineering, coding agents, and long-context retrieval. It delivers fast processing speeds and operates at a lower cost compared to many traditional models. Developers can access SubQ through APIs or integrate it into coding tools for enhanced workflows. Its architecture enables scalable AI reasoning without the limitations of standard transformer models.
  • 17
    ERNIE 5.1
    ERNIE 5.1 is Baidu’s latest large language model designed to deliver advanced reasoning, agentic AI capabilities, creative writing, and world knowledge performance while operating with significantly improved efficiency. The model builds on the foundation of ERNIE 5.0 while reducing total parameters and training costs, allowing it to achieve flagship-level intelligence at a fraction of the computational expense of comparable models. ERNIE 5.1 performs strongly across international benchmarks for reasoning, search, knowledge, and agentic tasks, ranking among the top global AI models and leading among Chinese-developed models on multiple leaderboards. The platform introduces a new fully asynchronous reinforcement learning infrastructure that improves training efficiency, scalability, and stability for complex long-horizon AI tasks. ERNIE 5.1 also features advanced creative writing capabilities.
  • 18
    Gemini 3.5 Pro
    Gemini 3.5 Pro is Google’s upcoming flagship AI model designed to deliver advanced reasoning, coding, and agent-based workflow capabilities for developers, enterprises, and general users. The model is part of the new Gemini 3.5 family introduced at Google I/O 2026, where Google highlighted improvements in intelligent task execution, long-context understanding, and AI-powered automation. Gemini 3.5 Pro is expected to build on the capabilities of Gemini 3.5 Flash by offering stronger reasoning performance, deeper contextual memory, and enhanced coding intelligence. Google positions the model as a major step toward more autonomous AI agents capable of managing complex workflows across productivity, software development, and research tasks. Reports suggest the platform will integrate closely with Google products, Gemini Spark, Antigravity, Google Search AI Mode, and enterprise tools.
  • 19
    GPT-5.6

    GPT-5.6

    OpenAI

    GPT-5.6 is a rumored next-generation AI model expected to continue OpenAI’s GPT-5 series with stronger reasoning, coding, and autonomous workflow capabilities. While OpenAI has not officially announced GPT-5.6, leaks and industry speculation suggest the model may already be in internal testing following the release of GPT-5.5 in April 2026. Reports indicate that GPT-5.6 could focus heavily on advanced software engineering, long-context reasoning, and improved AI agent orchestration for enterprise and developer workflows. The model is also expected to enhance multimodal intelligence, allowing for better handling of text, images, documents, and computer-use tasks. Some rumors mention expanded context windows, faster inference modes, and more efficient token usage compared to previous GPT-5 models. As of now, GPT-5.5 remains OpenAI’s latest officially released flagship model, and GPT-5.6 has not been confirmed publicly by the company.
  • 20
    MAI-Thinking-1

    MAI-Thinking-1

    Microsoft AI

    MAI-Thinking-1 is Microsoft AI’s reasoning model, built for complex problems that matter most, with competitive reasoning and strong software engineering performance in its weight class. It is a 35B-active, approximately 1T-total-parameter sparse Mixture of Experts model, giving it a smaller inference footprint than much larger models while still matching leading models on key software engineering benchmarks. Microsoft trained MAI-Thinking-1 from the ground up on enterprise-grade, clean, commercially licensed data, without distillation from third-party models, so its capabilities are learned rather than inherited. The model is part of Microsoft AI’s Hill-Climbing Machine, a co-designed development pipeline built to make every component of model development continually and reliably improve over time. MAI-Thinking-1 is designed for agentic coding environments where models must read code, edit files, run tests, observe failures, and recover from intermediate mistakes.
  • 21
    MAI-Code-1-Flash

    MAI-Code-1-Flash

    Microsoft AI

    MAI-Code-1-Flash is a Microsoft coding model built for fast, efficient assistance in everyday developer workflows. Built end-to-end by Microsoft using clean and appropriately licensed data, the model is rolling out to GitHub Copilot individual users in Visual Studio Code through the model picker and the default Auto picker. It is designed around the goal of delivering high-quality coding help with better efficiency, helping engineering teams write better code faster through a lightweight, agentic model integrated into GitHub Copilot and VS Code. MAI-Code-1-Flash was trained directly with GitHub Copilot production harnesses, allowing it to interact with surrounding tools and systems in real developer environments rather than being optimized only for static benchmarks. It supports agentic coding, strong instruction-following across single-turn and multi-turn scenarios, repository question answering, refactoring, telemetry-grounded tasks, and adaptive thinking.
  • 22
    North Mini Code
    North Mini Code is Cohere’s first agentic coding model for developers and the inaugural member of its next generation of powerful models. Small, efficient, and open-source, it is built for the sovereign developer ecosystem and designed to deliver strong software development performance without requiring extensive hardware. North Mini Code is a mixture-of-experts model with 30B total parameters and 3B active parameters, giving developers access to agentic coding capabilities in a compact and efficient form. The model is optimized for code generation, agentic software engineering, and terminal tasks, with a 256K total context length and up to 64K maximum generation. It is built for real-world developer workflows, including understanding and orchestrating sub-agents, mapping system architecture, running code reviews, and supporting coding agents that need to reason through complex software tasks.
  • 23
    LTM-1

    LTM-1

    Magic AI

    Magic’s LTM-1 enables 50x larger context windows than transformers. Magic's trained a Large Language Model (LLM) that’s able to take in the gigantic amounts of context when generating suggestions. For our coding assistant, this means Magic can now see your entire repository of code. Larger context windows can allow AI models to reference more explicit, factual information and their own action history. We hope to be able to utilize this research to improve reliability and coherence.
  • 24
    Samsung Gauss
    Samsung Gauss is a new AI model developed by Samsung Electronics. It is a large language model (LLM) that has been trained on a massive dataset of text and code. Samsung Gauss is able to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Samsung Gauss is still under development, but it has already learned to perform many kinds of tasks, including: Following instructions and completing requests thoughtfully. Answering your questions in a comprehensive and informative way, even if they are open ended, challenging, or strange. Generating different creative text formats, like poems, code, scripts, musical pieces, email, letters, etc. Here are some examples of what Samsung Gauss can do: Translation: Samsung Gauss can translate text between many different languages, including English, French, German, Spanish, Chinese, Japanese, and Korean. Coding: Samsung Gauss can generate code.
  • 25
    CodeGemma
    CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following. CodeGemma has 3 model variants, a 7B pre-trained variant that specializes in code completion and generation from code prefixes and/or suffixes, a 7B instruction-tuned variant for natural language-to-code chat and instruction following; and a state-of-the-art 2B pre-trained variant that provides up to 2x faster code completion. Complete lines, and functions, and even generate entire blocks of code, whether you're working locally or using Google Cloud resources. Trained on 500 billion tokens of primarily English language data from web documents, mathematics, and code, CodeGemma models generate code that's not only more syntactically correct but also semantically meaningful, reducing errors and debugging time.
  • 26
    OpenAI o4-mini
    The o4-mini model is a compact and efficient version of the o3 model, released following the launch of GPT-4.1. It offers enhanced reasoning capabilities, with improved performance in tasks that require complex reasoning and problem-solving. The o4-mini is designed to meet the growing demand for advanced AI solutions, serving as a more efficient alternative while maintaining the capabilities of its predecessor. This model is part of OpenAI's strategy to refine and advance their AI technologies ahead of the anticipated GPT-5 launch.
  • 27
    Grok 4.1
    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.
  • 28
    GPT-5.4

    GPT-5.4

    OpenAI

    GPT-5.4 is an advanced artificial intelligence model developed by OpenAI to support complex professional and technical work. The model combines improvements in reasoning, coding, and agent-based workflows into a single system designed for real-world productivity tasks. GPT-5.4 can generate, analyze, and edit documents, spreadsheets, presentations, and other work outputs with greater accuracy and efficiency. It also features improved tool integration, enabling the model to interact with software environments and external tools to complete multi-step workflows. With enhanced context capabilities supporting up to one million tokens, GPT-5.4 can process and reason over very large amounts of information. The model also improves factual accuracy and reduces errors compared to earlier versions. By combining strong reasoning, coding ability, and tool use, GPT-5.4 helps users complete complex tasks faster and with fewer iterations.
  • 29
    Claude Mythos

    Claude Mythos

    Anthropic

    Claude Mythos Preview is a highly advanced AI model developed with strong capabilities in cybersecurity, particularly in identifying and exploiting software vulnerabilities. It demonstrates the ability to autonomously discover zero-day vulnerabilities across major operating systems, browsers, and critical software systems. The model can also generate complex exploit chains, including privilege escalation and remote code execution attacks. Its capabilities extend beyond vulnerability detection to reverse engineering and exploit development in both open-source and closed-source environments. Mythos Preview operates through agentic workflows, enabling it to analyze codebases, test hypotheses, and validate exploits independently. These abilities represent a significant leap compared to previous models, which struggled with exploit generation. Overall, Claude Mythos Preview highlights a new era where AI can both strengthen and challenge global cybersecurity practices.
  • 30
    Claude Sonnet 4.8
    Claude Sonnet 4.8 is an advanced AI model designed to deliver strong performance across everyday tasks, professional workflows, and technical problem-solving. It offers improved reasoning, faster responses, and more reliable outputs compared to earlier Sonnet versions. The model excels at writing, coding, analysis, and general productivity tasks with a balanced approach to speed and quality. It supports multimodal capabilities, allowing it to understand and work with both text and images. Claude Sonnet 4.8 is built to follow instructions more accurately, reducing errors and improving consistency. It is optimized for real-world applications such as business operations, content creation, and software development. The model also includes safety and alignment improvements to ensure responsible usage. Overall, Claude Sonnet 4.8 provides a versatile and efficient AI solution for a wide range of use cases.
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