Alternatives to GPT-5.2-Codex

Compare GPT-5.2-Codex alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to GPT-5.2-Codex in 2025. Compare features, ratings, user reviews, pricing, and more from GPT-5.2-Codex competitors and alternatives in order to make an informed decision for your business.

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    Google AI Studio
    Google AI Studio is a comprehensive, web-based development environment that democratizes access to Google's cutting-edge AI models, notably the Gemini family, enabling a broad spectrum of users to explore and build innovative applications. This platform facilitates rapid prototyping by providing an intuitive interface for prompt engineering, allowing developers to meticulously craft and refine their interactions with AI. Beyond basic experimentation, AI Studio supports the seamless integration of AI capabilities into diverse projects, from simple chatbots to complex data analysis tools. Users can rigorously test different prompts, observe model behaviors, and iteratively refine their AI-driven solutions within a collaborative and user-friendly environment. This empowers developers to push the boundaries of AI application development, fostering creativity and accelerating the realization of AI-powered solutions.
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    Amp

    Amp

    Sourcegraph

    Amp by Sourcegraph is an advanced agentic coding tool designed to enhance software development speed, quality, and team collaboration. It leverages frontier AI models to perform autonomous reasoning, comprehensive code editing, and complex task execution. Developers can use Amp directly from their terminal via CLI or as a VS Code extension, eliminating the need to learn a new UI. The platform promotes sharing of workflows, context, and code changes to improve team efficiency and reuse successful patterns. Amp scales seamlessly from individual developers to large enterprises, offering enterprise-grade security, privacy, and compliance features. Users praise Amp for its smart, fast, and high-quality coding assistance that consistently outperforms competitors.
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    Claude Code

    Claude Code

    Anthropic

    Claude Code is an AI-powered coding assistant that brings Anthropic’s Claude directly to the developer’s terminal. It enables engineers to search, understand, and modify million-line codebases instantly using natural language. By integrating with your existing command-line tools, version control systems, and CI/CD pipelines, Claude Code fits seamlessly into any development workflow. Developers can triage issues, refactor code, and generate pull requests without ever leaving the terminal. With its deep contextual understanding, it performs multi-file edits and real-time code analysis while preserving accuracy and intent. It’s designed to make development faster, smarter, and friction-free for individuals and teams alike.
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    Claude Opus 4.5
    Claude Opus 4.5 is Anthropic’s newest flagship model, delivering major improvements in reasoning, coding, agentic workflows, and real-world problem solving. It outperforms previous models and leading competitors on benchmarks such as SWE-bench, multilingual coding tests, and advanced agent evaluations. Opus 4.5 also introduces stronger safety features, including significantly higher resistance to prompt injection and improved alignment across sensitive tasks. Developers gain new controls through the Claude API—like effort parameters, context compaction, and advanced tool use—allowing for more efficient, longer-running agentic workflows. Product updates across Claude, Claude Code, the Chrome extension, and Excel integrations expand how users interact with the model for software engineering, research, and everyday productivity. Overall, Claude Opus 4.5 marks a substantial step forward in capability, reliability, and usability for developers, enterprises, and end users.
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    Claude Sonnet 4.5
    Claude Sonnet 4.5 is Anthropic’s latest frontier model, designed to excel in long-horizon coding, agentic workflows, and intensive computer use while maintaining safety and alignment. It achieves state-of-the-art performance on the SWE-bench Verified benchmark (for software engineering) and leads on OSWorld (a computer use benchmark), with the ability to sustain focus over 30 hours on complex, multi-step tasks. The model introduces improvements in tool handling, memory management, and context processing, enabling more sophisticated reasoning, better domain understanding (from finance and law to STEM), and deeper code comprehension. It supports context editing and memory tools to sustain long conversations or multi-agent tasks, and allows code execution and file creation within Claude apps. Sonnet 4.5 is deployed at AI Safety Level 3 (ASL-3), with classifiers protecting against inputs or outputs tied to risky domains, and includes mitigations against prompt injection.
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    Gemini 3 Pro
    Gemini 3 Pro is Google’s most advanced multimodal AI model, built for developers who want to bring ideas to life with intelligence, precision, and creativity. It delivers breakthrough performance across reasoning, coding, and multimodal understanding—surpassing Gemini 2.5 Pro in both speed and capability. The model excels in agentic workflows, enabling autonomous coding, debugging, and refactoring across entire projects with long-context awareness. With superior performance in image, video, and spatial reasoning, Gemini 3 Pro powers next-generation applications in development, robotics, XR, and document intelligence. Developers can access it through the Gemini API, Google AI Studio, or Vertex AI, integrating seamlessly into existing tools and IDEs. Whether generating code, analyzing visuals, or building interactive apps from a single prompt, Gemini 3 Pro represents the future of intelligent, multimodal AI development.
    Starting Price: $19.99/month
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    GPT-5.1-Codex
    GPT-5.1-Codex is a specialized version of the GPT-5.1 model built for software engineering and agentic coding workflows. It is optimized for both interactive development sessions and long-horizon, autonomous execution of complex engineering tasks, such as building projects from scratch, developing features, debugging, performing large-scale refactoring, and code review. It supports tool-use, integrates naturally with developer environments, and adapts reasoning effort dynamically, moving quickly on simple tasks while spending more time on deep ones. The model is described as producing cleaner and higher-quality code outputs compared to general models, with closer adherence to developer instructions and fewer hallucinations. GPT-5.1-Codex is available via the Responses API route (rather than a standard chat API) and comes in variants including “mini” for cost-sensitive usage and “max” for the highest capability.
    Starting Price: $1.25 per input
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    GPT-5.1-Codex-Max
    GPT-5.1-Codex-Max is the high-capability variant of the GPT-5.1-Codex series designed specifically for software engineering and agentic code workflows. It builds on the base GPT-5.1 architecture with a focus on long-horizon tasks such as full project generation, large-scale refactoring, and autonomous multi-step bug and test management. It introduces adaptive reasoning, meaning the system dynamically allocates more compute for complex problems and less for simpler ones, to improve efficiency and output quality. It also supports tool use (IDE-integrated workflows, version control, CI/CD pipelines) and offers higher fidelity in code review, debugging, and agentic behavior than general-purpose models. Alongside Max, there are lighter variants such as Codex-Mini for cost-sensitive or scale use-cases. The GPT-5.1-Codex family is available in developer previews, including via integrations like GitHub Copilot.
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    Grok Code Fast 1
    Grok Code Fast 1 is a high-speed, economical reasoning model designed specifically for agentic coding workflows. Unlike traditional models that can feel slow in tool-based loops, it delivers near-instant responses, excelling in everyday software development tasks. Built from scratch with a programming-rich corpus and refined on real-world pull requests, it supports languages like TypeScript, Python, Java, Rust, C++, and Go. Developers can use it for everything from zero-to-one project building to precise bug fixes and codebase Q&A. With optimized inference and caching techniques, it achieves impressive responsiveness and a 90%+ cache hit rate when integrated with partners like GitHub Copilot, Cursor, and Cline. Offered at just $0.20 per million input tokens and $1.50 per million output tokens, Grok Code Fast 1 strikes a strong balance between speed, performance, and affordability.
    Starting Price: $0.20 per million input tokens
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    GPT‑5-Codex
    GPT-5-Codex is a version of GPT-5 further optimized for agentic coding within Codex, focusing on real-world software engineering tasks (building full projects from scratch, adding features & tests, debugging, large-scale refactors, and code reviews). Codex now moves faster, is more reliable, and works better in real-time across your development environments, whether in terminal/CLI, IDE extension, via the web, in GitHub, or even on mobile. GPT-5-Codex is the default model for cloud tasks and code review; developers can also opt to use it locally via Codex CLI or the IDE extension. It dynamically adjusts how much “reasoning time” it spends depending on task complexity; small, well-defined tasks are fast and snappy; more complex ones (refactors, large feature work) get more sustained effort. Code review is stronger; it catches critical bugs before shipping.
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    GPT-5-Codex-Mini
    GPT-5-Codex-Mini is a compact and cost-efficient version of GPT-5-Codex designed to deliver roughly four times more usage with only a slight tradeoff in capability. It’s optimized for handling routine or lighter programming tasks while maintaining reliable output quality. Developers can access it through the CLI and IDE extension by signing in with ChatGPT, with API access coming soon. The system automatically suggests switching to GPT-5-Codex-Mini when users near 90% of their rate limits, helping extend uninterrupted usage. ChatGPT Plus, Business, and Edu users receive 50% higher rate limits, offering more flexibility for frequent workflows. Pro and Enterprise accounts are prioritized for faster processing, ensuring smoother, high-speed performance across larger workloads.
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    Qwen Code
    Qwen3‑Coder is an agentic code model available in multiple sizes, led by the 480B‑parameter Mixture‑of‑Experts variant (35B active) that natively supports 256K‑token contexts (extendable to 1M) and achieves state‑of‑the‑art results on Agentic Coding, Browser‑Use, and Tool‑Use tasks comparable to Claude Sonnet 4. Pre‑training on 7.5T tokens (70 % code) and synthetic data cleaned via Qwen2.5‑Coder optimized both coding proficiency and general abilities, while post‑training employs large‑scale, execution‑driven reinforcement learning and long‑horizon RL across 20,000 parallel environments to excel on multi‑turn software‑engineering benchmarks like SWE‑Bench Verified without test‑time scaling. Alongside the model, the open source Qwen Code CLI (forked from Gemini Code) unleashes Qwen3‑Coder in agentic workflows with customized prompts, function calling protocols, and seamless integration with Node.js, OpenAI SDKs, and more.
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    Qwen3-Coder
    Qwen3‑Coder is an agentic code model available in multiple sizes, led by the 480B‑parameter Mixture‑of‑Experts variant (35B active) that natively supports 256K‑token contexts (extendable to 1M) and achieves state‑of‑the‑art results comparable to Claude Sonnet 4. Pre‑training on 7.5T tokens (70 % code) and synthetic data cleaned via Qwen2.5‑Coder optimized both coding proficiency and general abilities, while post‑training employs large‑scale, execution‑driven reinforcement learning, scaling test‑case generation for diverse coding challenges, and long‑horizon RL across 20,000 parallel environments to excel on multi‑turn software‑engineering benchmarks like SWE‑Bench Verified without test‑time scaling. Alongside the model, the open source Qwen Code CLI (forked from Gemini Code) unleashes Qwen3‑Coder in agentic workflows with customized prompts, function calling protocols, and seamless integration with Node.js, OpenAI SDKs, and environment variables.
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    Codex CLI
    Codex CLI is an open-source, lightweight coding agent that integrates directly into your terminal, designed to help developers write, edit, and understand code efficiently. By pairing with Codex CLI, developers can leverage the power of AI to streamline their workflow, get real-time code suggestions, and improve their coding accuracy, all from within their command line interface. It provides a seamless, accessible way to enhance coding productivity while staying in the environment developers are already comfortable with.
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    OpenAI Codex
    OpenAI Codex is an advanced AI coding tool designed to assist software developers by automating many tasks in their coding workflow. It allows users to delegate tasks such as writing features, answering codebase questions, running tests, and proposing pull requests (PRs) for review. Codex works in parallel, handling multiple tasks simultaneously in secure cloud sandboxes preloaded with your repository. This tool helps developers move through their backlog faster and more efficiently, making it an invaluable asset for teams looking to streamline their development process.
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    CodeGen

    CodeGen

    Salesforce

    CodeGen is an open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.
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    Aardvark

    Aardvark

    OpenAI

    Aardvark is an autonomous security-research agent powered by GPT-5, designed to act like a human security researcher, continuously analyzing source-code repositories, developing threat models, scanning commits for vulnerabilities, validating exploitability in sandboxed environments, and proposing targeted patches for human review. Unlike traditional tools that rely purely on fuzzing or software-composition analysis, Aardvark uses an LLM-based reasoning pipeline to interpret code behavior and integrate directly into existing developer workflows (e.g., GitHub, code-review pipelines, Codex for patch generation). It supports historical scanning of entire repositories at initial connection, commit-level scanning thereafter, automatic patch generation and verification, and human-auditable annotations for each finding. Early internal benchmarks at OpenAI show detection recall of 92% in repositories seeded with known or synthetic vulnerabilities.
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    GLM-4.7

    GLM-4.7

    Zhipu AI

    GLM-4.7 is an advanced large language model designed to significantly elevate coding, reasoning, and agentic task performance. It delivers major improvements over GLM-4.6 in multilingual coding, terminal-based tasks, and real-world software engineering benchmarks such as SWE-bench and Terminal Bench. GLM-4.7 supports “thinking before acting,” enabling more stable, accurate, and controllable behavior in complex coding and agent workflows. The model also introduces strong gains in UI and frontend generation, producing cleaner webpages, better layouts, and more polished slides. Enhanced tool-using capabilities allow GLM-4.7 to perform more effectively in web browsing, automation, and agent benchmarks. Its reasoning and mathematical performance has improved substantially, showing strong results on advanced evaluation suites. GLM-4.7 is available via Z.ai, API platforms, coding agents, and local deployment for flexible adoption.
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    SuperAGI SuperCoder
    SuperAGI SuperCoder is an open-source autonomous system that combines AI-native dev platform & AI agents to enable fully autonomous software development starting with python language & frameworks SuperCoder 2.0 leverages LLMs & Large Action Model (LAM) fine-tuned for python code generation leading to one shot or few shot python functional coding with significantly higher accuracy across SWE-bench & Codebench As an autonomous system, SuperCoder 2.0 combines software guardrails specific to development framework starting with Flask & Django with SuperAGI’s Generally Intelligent Developer Agents to deliver complex real world software systems SuperCoder 2.0 deeply integrates with existing developer stack such as Jira, Github or Gitlab, Jenkins, CSPs and QA solutions such as BrowserStack /Selenium Clouds to ensure a seamless software development experience
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    Devstral Small 2
    Devstral Small 2 is the compact, 24 billion-parameter variant of the new coding-focused model family from Mistral AI, released under the permissive Apache 2.0 license to enable both local deployment and API use. Alongside its larger sibling (Devstral 2), this model brings “agentic coding” capabilities to environments with modest compute: it supports a large 256K-token context window, enabling it to understand and make changes across entire codebases. On the standard code-generation benchmark (SWE-Bench Verified), Devstral Small 2 scores around 68.0%, placing it among open-weight models many times its size. Because of its reduced size and efficient design, Devstral Small 2 can run on a single GPU or even CPU-only setups, making it practical for developers, small teams, or hobbyists without access to data-center hardware. Despite its compact footprint, Devstral Small 2 retains key capabilities of larger models; it can reason across multiple files and track dependencies.
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    GPT-4.1

    GPT-4.1

    OpenAI

    GPT-4.1 is an advanced AI model from OpenAI, designed to enhance performance across key tasks such as coding, instruction following, and long-context comprehension. With a large context window of up to 1 million tokens, GPT-4.1 can process and understand extensive datasets, making it ideal for tasks like software development, document analysis, and AI agent workflows. Available through the API, GPT-4.1 offers significant improvements over previous models, excelling at real-world applications where efficiency and accuracy are crucial.
    Starting Price: $2 per 1M tokens (input)
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    CodeX

    CodeX

    SmallDay IT Services

    CodexPro is a revolutionary coding assessment solution designed for hiring managers and educational institutes. With an intuitive interface, CodexPro simplifies the evaluation process for both assessors and candidates, making it easy to navigate and evaluate coding skills efficiently. In addition to coding assessments, CodexPro offers English tests, Data Interpretation tests, Arithmetic tests, and Logical Reasoning tests, other essential skills for the industry. This comprehensive suite ensures thorough assessment across multiple domains, providing a holistic view of skills and knowledge. CodexPro stands out for its precision. Accurate evaluations are crucial for selecting candidates or gauging students' progress. Our platform offers industry-relevant coding challenges, advanced analytics, and insightful reports to gain deep insights into performance, strengths, and areas for improvement.
    Starting Price: Free 200 candidates per month
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    Devstral

    Devstral

    Mistral AI

    Devstral is an open source, agentic large language model (LLM) developed by Mistral AI in collaboration with All Hands AI, specifically designed for software engineering tasks. It excels at navigating complex codebases, editing multiple files, and resolving real-world issues, outperforming all open source models on the SWE-Bench Verified benchmark with a score of 46.8%. Devstral is fine-tuned from Mistral-Small-3.1 and features a long context window of up to 128,000 tokens. It is optimized for local deployment on high-end hardware, such as a Mac with 32GB RAM or an Nvidia RTX 4090 GPU, and is compatible with inference frameworks like vLLM, Transformers, and Ollama. Released under the Apache 2.0 license, Devstral is available for free and can be accessed via Hugging Face, Ollama, Kaggle, Unsloth, and LM Studio.
    Starting Price: $0.1 per million input tokens
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    StarCoder

    StarCoder

    BigCode

    StarCoder and StarCoderBase are Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks. Similar to LLaMA, we trained a ~15B parameter model for 1 trillion tokens. We fine-tuned StarCoderBase model for 35B Python tokens, resulting in a new model that we call StarCoder. We found that StarCoderBase outperforms existing open Code LLMs on popular programming benchmarks and matches or surpasses closed models such as code-cushman-001 from OpenAI (the original Codex model that powered early versions of GitHub Copilot). With a context length of over 8,000 tokens, the StarCoder models can process more input than any other open LLM, enabling a wide range of interesting applications. For example, by prompting the StarCoder models with a series of dialogues, we enabled them to act as a technical assistant.
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    Cosine Genie
    Whether it’s high-level or nuanced, Cosine can understand and provide superhuman level answers. We're not just an LLM wrapper – we combine multiple heuristics including static analysis, semantic search and others. Simply ask Cosine how to add a new feature or modify existing code and we’ll generate a step by step guide. Cosine indexes and understands your codebase on multiple levels. From a graph relationship between files and functions to a deep semantic understanding of the code, Cosine can answer any question you have about your codebase. Genie is the best AI software engineer in the world by far - achieving a 30% eval score on the industry standard benchmark SWE-Bench. Genie is able to solve bugs, build features, refactor code, and everything in between either fully autonomously or paired with the user, like working with a colleague, not just a copilot.
    Starting Price: $20/month
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    Claude Opus 4.1
    Claude Opus 4.1 is an incremental upgrade to Claude Opus 4 that boosts coding, agentic reasoning, and data-analysis performance without changing deployment complexity. It raises coding accuracy to 74.5 percent on SWE-bench Verified and sharpens in-depth research and detailed tracking for agentic search tasks. GitHub reports notable gains in multi-file code refactoring, while Rakuten Group highlights its precision in pinpointing exact corrections within large codebases without introducing bugs. Independent benchmarks show about a one-standard-deviation improvement on junior developer tests compared to Opus 4, mirroring major leaps seen in prior Claude releases. Opus 4.1 is available now to paid Claude users, in Claude Code, and via the Anthropic API (model ID claude-opus-4-1-20250805), as well as through Amazon Bedrock and Google Cloud Vertex AI, and integrates seamlessly into existing workflows with no additional setup beyond selecting the new model.
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    Code Snippets AI

    Code Snippets AI

    Code Snippets AI

    Turn your questions into code. Easily store and fetch your snippets. Collaborate with your team. Powered by ChatGPT & our fine-tuned GPT3 model. Gain a deeper understanding of your code to further your knowledge. Increase the quality of your code with our refactor and debug features. Securely share code snippets with your team, without losing formatting. We use ChatGPT & our fine-tuned GPT3 Model, which provides faster and more accurate responses to your questions, compared to Codex apps. Create documentation, refactor, debug, and generate code with the click of a button. We use a fine-tuned AI model trained on GPT3, which provides faster and more accurate responses to your questions, compared to Codex apps. Save your code from your IDE straight into your library with our VSCode extension. Search snippets by language, name, or folder. Create your own folder structure to suit your needs. We use ChatGPT & our fine-tuned GPT3 Model, which provides faster and more accurate responses.
    Starting Price: $2 per month
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    Solar Pro 2

    Solar Pro 2

    Upstage AI

    Solar Pro 2 is Upstage’s latest frontier‑scale large language model, designed to power complex tasks and agent‑like workflows across domains such as finance, healthcare, and legal. Packaged in a compact 31 billion‑parameter architecture, it delivers top‑tier multilingual performance, especially in Korean, where it outperforms much larger models on benchmarks like Ko‑MMLU, Hae‑Rae, and Ko‑IFEval, while also excelling in English and Japanese. Beyond superior language understanding and generation, Solar Pro 2 offers next‑level intelligence through an advanced Reasoning Mode that significantly boosts multi‑step task accuracy on challenges ranging from general reasoning (MMLU, MMLU‑Pro, HumanEval) to complex mathematics (Math500, AIME) and software engineering (SWE‑Bench Agentless), achieving problem‑solving efficiency comparable to or exceeding that of models twice its size. Enhanced tool‑use capabilities enable the model to interact seamlessly with external APIs and data sources.
    Starting Price: $0.1 per 1M tokens
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    Emdash

    Emdash

    Emdash

    Emdash is an orchestration layer that lets you run multiple coding agents in parallel, each in its own isolated Git worktree, so you can simultaneously spin up different agents to tackle independent subtasks or experiments without interference. It’s provider-agnostic, meaning you can pick from various AI models and CLIs (for example, Claude Code, Codex, and others) to fit your workflow. With Emdash, you can assign issues or tickets (from Linear, GitHub, or Jira) directly to a chosen agent, then watch multiple agents operate side by side in real time. The UI shows live agent status and activity, and once agents generate code, you can review diffs, comment, and open pull requests, all without leaving Emdash. Because every agent runs in a separate worktree, changes stay sandboxed and comparable, enabling you to test different implementations or strategies side-by-side safely.
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    Codestral Embed
    Codestral Embed is Mistral AI's first embedding model, specialized for code, optimized for high-performance code retrieval and semantic understanding. It significantly outperforms leading code embedders in the market today, such as Voyage Code 3, Cohere Embed v4.0, and OpenAI’s large embedding model. Codestral Embed can output embeddings with different dimensions and precisions; for instance, with a dimension of 256 and int8 precision, it still performs better than any model from competitors. The dimensions of the embeddings are ordered by relevance, allowing users to choose the first n dimensions for a smooth trade-off between quality and cost. It excels in retrieval use cases on real-world code data, particularly in benchmarks like SWE-Bench, which is based on real-world GitHub issues and corresponding fixes, and Text2Code (GitHub), relevant for providing context for code completion or editing.
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    CodeNext

    CodeNext

    CodeNext

    CodeNext.ai is an AI-powered coding assistant designed specifically for Xcode developers, offering context-aware code completion and agentic chat functionalities. It supports a wide range of leading AI models, including OpenAI, Azure OpenAI, Google AI, Mistral, Anthropic, Deepseek, Ollama, and more, providing developers with the flexibility to choose and switch between models as needed. It delivers intelligent, real-time code suggestions as you type, enhancing productivity and coding efficiency. Its agentic chat feature allows developers to interact in natural language to write code, fix bugs, refactor, and perform various coding tasks within or beyond the codebase. CodeNext.ai includes custom chat plugins that enable the execution of terminal commands and shortcuts directly within the chat interface, streamlining the development workflow.
    Starting Price: $15 per month
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    Augment Code

    Augment Code

    Augment Code

    Augment Code is an AI-powered coding agent designed specifically for professional software engineers working with large codebases. It integrates seamlessly with popular IDEs like Visual Studio Code, IntelliJ IDEA, and Vim, offering tools for SDK migration, code refactoring, and documentation. Augment Code enhances developers’ productivity by understanding their unique code style and context, providing personalized recommendations and explanations. The platform supports over 100 native and MCP tools, allowing engineers to debug and code more efficiently without switching between different applications.
    Starting Price: $50 per developer per month
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    Claude Sonnet 4
    Claude Sonnet 4, the latest evolution of Anthropic’s language models, offers a significant upgrade in coding, reasoning, and performance. Designed for diverse use cases, Sonnet 4 builds upon the success of its predecessor, Claude Sonnet 3.7, delivering more precise responses and better task execution. With a state-of-the-art 72.7% performance on the SWE-bench, it stands out in agentic scenarios, offering enhanced steerability and clear reasoning capabilities. Whether handling software development, multi-feature app creation, or complex problem-solving, Claude Sonnet 4 ensures higher code quality, reduced errors, and a smoother development process.
    Starting Price: $3 / 1 million tokens (input)
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    MiniMax-M2.1
    MiniMax-M2.1 is an open-source, agentic large language model designed for advanced coding, tool use, and long-horizon planning. It was released to the community to make high-performance AI agents more transparent, controllable, and accessible. The model is optimized for robustness in software engineering, instruction following, and complex multi-step workflows. MiniMax-M2.1 supports multilingual development and performs strongly across real-world coding scenarios. It is suitable for building autonomous applications that require reasoning, planning, and execution. The model weights are fully open, enabling local deployment and customization. MiniMax-M2.1 represents a major step toward democratizing top-tier agent capabilities.
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    Crush

    Crush

    Charm

    Crush is a glamorous AI coding agent that lives right in your terminal, seamlessly connecting your tools, code, and workflows with any Large Language Model (LLM) of your choice. It offers multi-model flexibility, letting you choose from a variety of LLMs or add your own using OpenAI or Anthropic-compatible APIs, and supports mid-session switching between them while preserving context. Crush is session-based, enabling multiple project-specific contexts to coexist. Powered by Language Server Protocol (LSP) enhancements, it incorporates coding-aware context just like a developer’s editor. It's highly extensible via Model Context Protocol (MCP) plugins using HTTP, stdio, or SSE for added capabilities. Crush runs anywhere, leveraging Charm’s sleek Bubble Tea-based TUI for a polished terminal user experience. Written in Go and MIT-licensed (with FSL-1.1 for trademarks), enabling developers to stay in their terminal while taking advantage of expressive AI coding assistance.
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    Aider

    Aider

    Aider AI

    Aider lets you pair program with LLMs, to edit code in your local git repository. Start a new project or work with an existing git repo. Aider works best with GPT-4o & Claude 3.5 Sonnet and can connect to almost any LLM. Aider has one of the top scores on SWE Bench. SWE Bench is a challenging software engineering benchmark where aider solved real GitHub issues from popular open source projects like django, scikitlearn, matplotlib, etc.
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    CoinCodex

    CoinCodex

    CoinCodex

    CoinCodex is your all-in-one platform for real-time financial data, market insights, and investment tools. Track more than 40,000 cryptocurrencies with detailed charts, live prices, market caps, trading volumes, all-time highs, and customizable time frames. Compare multiple coins on a single chart or explore full historical price data for deeper analysis. Beyond crypto, CoinCodex also provides live pricing and forecasts for stocks, forex, gold, and silver, giving you a complete overview of global markets in one place. To support your investment strategy, CoinCodex includes a portfolio tracker, extensive historical datasets, and a suite of financial calculators that help you analyze performance, plan investments, and make informed decisions.
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    Grok 4.1 Fast
    Grok 4.1 Fast is the newest xAI model designed to deliver advanced tool-calling capabilities with a massive 2-million-token context window. It excels at complex real-world tasks such as customer support, finance, troubleshooting, and dynamic agent workflows. The model pairs seamlessly with the new Agent Tools API, which enables real-time web search, X search, file retrieval, and secure code execution. This combination gives developers the power to build fully autonomous, production-grade agents that plan, reason, and use tools effectively. Grok 4.1 Fast is trained with long-horizon reinforcement learning, ensuring stable multi-turn accuracy even across extremely long prompts. With its speed, cost-efficiency, and high benchmark scores, it sets a new standard for scalable enterprise-grade AI agents.
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    DeepCoder

    DeepCoder

    Agentica Project

    DeepCoder is a fully open source code-reasoning and generation model released by Agentica Project in collaboration with Together AI. It is fine-tuned from DeepSeek-R1-Distilled-Qwen-14B using distributed reinforcement learning, achieving a 60.6% accuracy on LiveCodeBench (representing an 8% improvement over the base), a performance level that matches that of proprietary models such as o3-mini (2025-01-031 Low) and o1 while using only 14 billion parameters. It was trained over 2.5 weeks on 32 H100 GPUs with a curated dataset of roughly 24,000 coding problems drawn from verified sources (including TACO-Verified, PrimeIntellect SYNTHETIC-1, and LiveCodeBench submissions), each problem requiring a verifiable solution and at least five unit tests to ensure reliability for RL training. To handle long-range context, DeepCoder employs techniques such as iterative context lengthening and overlong filtering.
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    VibeKit

    VibeKit

    VibeKit

    VibeKit is a simple, open source SDK for safely running Codex and Claude Code agents in secure, customizable sandboxes. It enables you to embed coding agents directly in your app or workflow via a drop‑in SDK. import VibeKit and VibeKitConfig, and call generateCode with prompts, modes, and streaming callbacks for live output handling. VibeKit runs code in fully isolated private sandboxes, supports customizable environments where you can install packages, and is model‑agnostic, letting you choose any compatible Codex or Claude model. It streams agent output efficiently, maintains full prompt and code history, provides async run handling, integrates with GitHub for commits, branches, and pull requests, and supports telemetry and tracing (via OpenTelemetry). Compatible sandbox providers include E2B (today), with Daytona, Modal, Fly.io, and others coming soon, plus support for any runtime that meets your security needs.
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    Qwen2.5-Max
    Qwen2.5-Max is a large-scale Mixture-of-Experts (MoE) model developed by the Qwen team, pretrained on over 20 trillion tokens and further refined through Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). In evaluations, it outperforms models like DeepSeek V3 in benchmarks such as Arena-Hard, LiveBench, LiveCodeBench, and GPQA-Diamond, while also demonstrating competitive results in other assessments, including MMLU-Pro. Qwen2.5-Max is accessible via API through Alibaba Cloud and can be explored interactively on Qwen Chat.
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    SWE-1

    SWE-1

    Windsurf

    SWE-1 is the first family of software engineering models developed by Windsurf, designed to optimize the entire software engineering process. Comprising three models—SWE-1, SWE-1-lite, and SWE-1-mini—this innovative family of models tackles more than just coding by supporting a wide range of engineering tasks. SWE-1 outperforms other models, providing powerful, multi-surface, long-horizon task management and AI-driven insights that significantly accelerate software development. This groundbreaking approach allows for more efficient problem-solving and an AI-powered workflow that integrates seamlessly with user actions.
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    Genie AI

    Genie AI

    Genie AI

    Genie AI is a Visual Studio Code extension that integrates OpenAI's GPT models, including GPT-4, GPT-3.5, GPT-3, and Codex, directly into the development environment. This integration enhances the coding experience by providing features such as code generation, error explanation, and code fixes. Users can generate commit messages from git changes, store conversation history locally, and utilize the extension in the problems window to address compile-time errors. Genie AI supports streaming answers, allowing users to receive real-time responses to prompts within the editor or sidebar conversation. It also offers compatibility with Azure OpenAI Service deployments, enabling the use of custom models. Additional functionalities include customizable system messages, quick fixes for code issues, and the ability to export conversation history in Markdown format. The extension is designed to enhance developer productivity by integrating advanced AI capabilities into the coding workflow.
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    Auggie CLI

    Auggie CLI

    Augment Code

    Auggie CLI brings Augment’s intelligent coding agent directly into your terminal by leveraging its powerful context engine to analyze code, make edits, and execute tools both interactively and within automated workflows. Developers can install it via npm (requiring Node.js 22+ and a compatible shell), then launch a full-screen interactive session using auggie, complete with real-time streaming, visual progress, and conversational tooling, for debugging, feature development, PR review, or triaging alerts. For automation, Auggie offers streamlined modes ideal for CI/CD pipelines and background tasks. The CLI also supports custom slash commands for repeatable workflows, integrates with external tools and systems via native integrations and Model Context Protocol (MCP) servers, and can be scripted in pipelines or GitHub Actions for tasks like auto-generating PR descriptions.
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    Devstral 2

    Devstral 2

    Mistral AI

    Devstral 2 is a next-generation, open source agentic AI model tailored for software engineering: it doesn’t just suggest code snippets, it understands and acts across entire codebases, enabling multi-file edits, bug fixes, refactoring, dependency resolution, and context-aware code generation. The Devstral 2 family includes a large 123-billion-parameter model as well as a smaller 24-billion-parameter variant (“Devstral Small 2”), giving teams flexibility; the larger model excels in heavy-duty coding tasks requiring deep context, while the smaller one can run on more modest hardware. With a vast context window of up to 256 K tokens, Devstral 2 can reason across extensive repositories, track project history, and maintain a consistent understanding of lengthy files, an advantage for complex, real-world projects. The CLI tracks project metadata, Git statuses, and directory structure to give the model context, making “vibe-coding” more powerful.
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    Kiro

    Kiro

    Amazon Web Services

    Kiro is an AI‑powered integrated development environment that brings structure to AI‑driven coding by converting natural‑language prompts into clear requirements, system designs, and discrete implementation tasks validated by robust tests. Built from the ground up for agentic workflows, it features spec‑driven development, multimodal chat, “agent hooks” that trigger background tasks on events like file saves, and an autopilot mode that autonomously runs large scripts while keeping you in control. With smart context management, Kiro reduces repetitive prompts and helps implement complex features across large codebases. Native MCP integrations let you connect to documentation, databases, and APIs, and you can guide development with images of UI designs or architecture diagrams. Enterprise‑grade security and privacy ensure safe deployment, while support for Claude Sonnet models, Open VSX plugins, and existing VS Code settings delivers a familiar yet AI‑supercharged experience.
    Starting Price: $19 per month
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    Roo Code

    Roo Code

    Roo Code

    ​Roo Code, formerly known as Roo Cline, is an AI-powered autonomous coding agent integrated into Visual Studio Code, designed to enhance software development efficiency. It facilitates natural language interactions, enabling users to generate code, refactor existing code, debug, and update documentation seamlessly. It can read and write files directly within the workspace, execute terminal commands, and automate browser actions. It supports integration with any OpenAI-compatible or custom APIs/models and allows customization through various modes, including Code Mode for general coding tasks, Architect Mode for system design, Ask Mode for inquiries, Debug Mode for troubleshooting, and user-defined Custom Modes for specialized tasks. Roo Code also features the Model Context Protocol (MCP), extending its capabilities by integrating with external tools and APIs.
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    OpenCode

    OpenCode

    Anomaly Innovations

    OpenCode is the AI coding agent purpose-built for the terminal. It delivers a responsive, themeable terminal UI that feels native while streamlining your workflow. With LSP auto-loading, it ensures the right language servers are always available for accurate, context-aware coding support. Developers can spin up multiple AI agents in parallel sessions on the same project, maximizing productivity. Shareable links make it easy to reference, debug, or collaborate across sessions. Supporting Claude Pro and 75+ LLM providers via Models.dev, OpenCode gives you full freedom to choose your coding companion.
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    TRAE SOLO
    TRAE SOLO is described as a responsive coding agent built for real-world software development, seamlessly integrating into a developer’s full stack, editor, terminal, browser, documentation, design tools, and deployments, to bring ideas from concept to shipped reality. SOLO enables natural-language or voice-based input, letting you speak your requirements while it breaks down ideas into structured formats, selects the right context and tools, executes tasks across browsers, editors and terminals, autonomously writes and reviews code, handles testing and optimization, and deploys the final result, all visible in one unified workspace where you can switch between AI-led and manual modes at any time. It supports multiple agents working in parallel, each with its own model and context, giving you the flexibility to pick the best model for the task, monitor each agent’s progress in real time, and intervene or redirect as needed.
    Starting Price: $3 per month
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    Kimi K2 Thinking

    Kimi K2 Thinking

    Moonshot AI

    Kimi K2 Thinking is an advanced open source reasoning model developed by Moonshot AI, designed specifically for long-horizon, multi-step workflows where the system interleaves chain-of-thought processes with tool invocation across hundreds of sequential tasks. The model uses a mixture-of-experts architecture with a total of 1 trillion parameters, yet only about 32 billion parameters are activated per inference pass, optimizing efficiency while maintaining vast capacity. It supports a context window of up to 256,000 tokens, enabling the handling of extremely long inputs and reasoning chains without losing coherence. Native INT4 quantization is built in, which reduces inference latency and memory usage without performance degradation. Kimi K2 Thinking is explicitly built for agentic workflows; it can autonomously call external tools, manage sequential logic steps (up to and typically between 200-300 tool calls in a single chain), and maintain consistent reasoning.