Alternatives to GPT‑5.3‑Codex‑Spark
Compare GPT‑5.3‑Codex‑Spark alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to GPT‑5.3‑Codex‑Spark in 2026. Compare features, ratings, user reviews, pricing, and more from GPT‑5.3‑Codex‑Spark competitors and alternatives in order to make an informed decision for your business.
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SWE-1.5
Cognition
SWE-1.5 is the latest agent-model release by Cognition, purpose-built for software engineering and characterized by a “frontier-size” architecture comprising hundreds of billions of parameters and optimized end-to-end (model, inference engine, and agent harness) for both speed and intelligence. It achieves near-state-of-the-art coding performance and sets a new benchmark in latency, delivering inference speeds up to 950 tokens/second, roughly six times faster than its predecessor Haiku 4.5 and thirteen times faster than Sonnet 4.5. The model was trained using extensive reinforcement learning in realistic coding-agent environments with multi-turn workflows, unit tests, quality rubrics, and browser-based agentic execution; it also benefits from tightly integrated software tooling and high-throughput hardware (including thousands of GB200 NVL72 chips and a custom hypervisor infrastructure). -
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SWE-1.6
Cognition
SWE-1.6 is an engineering–focused AI model developed by Cognition and integrated into the Windsurf environment, designed to optimize both raw intelligence and what the company calls “model UX,” or the overall feel and efficiency of interacting with an AI agent. It represents a new iteration in the SWE model family, improving performance on benchmarks such as SWE-Bench Pro by over 10% compared to SWE-1.5 while maintaining similar underlying capabilities. It was trained from scratch to jointly improve reasoning quality and user experience, addressing issues observed in earlier versions such as overthinking simple problems, taking too many steps, looping in repetitive reasoning, and relying excessively on terminal commands instead of specialized tools. SWE-1.6 introduces behavioral improvements such as more frequent parallel tool usage, faster context retrieval, and reduced need for user input, resulting in smoother and more efficient workflows. -
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Claude Sonnet 4.5
Anthropic
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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Claude Sonnet 4.6
Anthropic
Claude Sonnet 4.6 is Anthropic’s most advanced Sonnet model to date, delivering significant upgrades across coding, computer use, long-context reasoning, agent planning, and knowledge work. It introduces a 1 million token context window in beta, allowing users to analyze entire codebases, lengthy contracts, or large research collections in a single session. The model demonstrates major improvements in instruction following, consistency, and reduced hallucinations compared to previous Sonnet versions. In developer testing, users strongly preferred Sonnet 4.6 over Sonnet 4.5 and even favored it over Opus 4.5 in many coding scenarios. Its enhanced computer-use capabilities enable it to interact with real software interfaces similarly to a human, improving automation for legacy systems without APIs. Sonnet 4.6 also performs strongly on major benchmarks, approaching Opus-level intelligence at a more accessible price point. -
5
Claude Opus 4.5
Anthropic
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 Opus 4.6
Anthropic
Claude Opus 4.6 is an advanced AI model developed by Anthropic, designed for high-level reasoning, coding, and knowledge work tasks. It introduces significant improvements in coding, debugging, and code review capabilities. The model can handle long, complex workflows and sustain agentic tasks with greater reliability. It features a 1 million token context window in beta, enabling it to process and retain large amounts of information. Claude Opus 4.6 is optimized for tasks such as financial analysis, research, and document creation. It also integrates with tools like Excel and PowerPoint for enhanced productivity. Overall, it is a state-of-the-art AI model built for complex, real-world professional applications. -
7
Codex CLI
OpenAI
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.Starting Price: Free -
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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.Starting Price: Free -
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GLM-5
Zhipu AI
GLM-5 is Z.ai’s latest large language model built for complex systems engineering and long-horizon agentic tasks. It scales significantly beyond GLM-4.5, increasing total parameters and training data while integrating DeepSeek Sparse Attention to reduce deployment costs without sacrificing long-context capacity. The model combines enhanced pre-training with a new asynchronous reinforcement learning infrastructure called slime, improving training efficiency and post-training refinement. GLM-5 achieves best-in-class performance among open-source models across reasoning, coding, and agent benchmarks, narrowing the gap with leading frontier models. It ranks highly on evaluations such as Vending Bench 2, demonstrating strong long-term planning and operational capabilities. The model is open-sourced under the MIT License.Starting Price: Free -
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DeepSeek-V4
DeepSeek
DeepSeek V4 is an advanced AI model designed to push the boundaries of large-scale artificial intelligence with an estimated 1 trillion parameters. It utilizes a Mixture-of-Experts architecture, activating only a fraction of its parameters per task to improve efficiency. The model supports a massive context window of up to 1 million tokens, enabling it to process long documents and complex codebases. It is natively multimodal, allowing it to understand and generate text, images, audio, and video. DeepSeek V4 introduces innovations such as Engram memory, sparse attention mechanisms, and improved training stability techniques. It is expected to deliver high performance in areas like software engineering and reasoning while maintaining lower operational costs. Overall, DeepSeek V4 aims to combine scalability, efficiency, and affordability to compete with leading AI models.Starting Price: Free -
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Gemini 3 Pro
Google
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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Gemini 3.1 Flash-Lite
Google
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. -
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Gemini 3.1 Pro
Google
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, Vertex AI, and Android Studio. With expanded access for Google AI Pro and Ultra users, 3.1 Pro sets a stronger baseline for ambitious agentic workflow & advanced applications. -
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GPT-5.2-Codex
OpenAI
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. -
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GPT-5.3-Codex
OpenAI
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. -
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GPT-5.3 Instant
OpenAI
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
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. -
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GPT-5.4 Pro
OpenAI
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. -
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GPT‑5.4 Thinking
OpenAI
GPT-5.4 Thinking is an advanced reasoning-focused AI model available within ChatGPT, designed to help users complete complex professional tasks more effectively. It combines improvements in reasoning, coding, and agent-based workflows to provide more accurate and reliable outputs. The model can present an upfront outline of its reasoning process, allowing users to adjust instructions while it is generating a response. This capability helps produce results that better align with user goals without requiring multiple follow-up prompts. GPT-5.4 Thinking also improves deep web research, enabling it to locate and synthesize information from multiple sources more efficiently. With stronger context management, it can handle longer conversations and complex problem-solving tasks with greater coherence. These capabilities make GPT-5.4 Thinking well suited for professional knowledge work and advanced analytical tasks. -
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GPT-5.4 mini
OpenAI
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
OpenAI
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. -
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Grok 4.1
xAI
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. -
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Grok 4.20
xAI
Grok 4.20 is an advanced artificial intelligence model developed by xAI to elevate reasoning and natural language understanding. Built on the high-performance Colossus supercomputer, it is engineered for speed, scale, and accuracy. Grok 4.20 processes multimodal inputs such as text and images, with video support planned for future releases. The model excels in scientific, technical, and linguistic tasks, delivering highly precise and context-aware responses. Its architecture supports deep reasoning and sophisticated problem-solving capabilities. Enhanced moderation improves output reliability and reduces bias compared to earlier versions. Overall, Grok 4.20 represents a significant step toward more human-like AI reasoning and interpretation. -
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Grok Code Fast 1
xAI
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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Kimi K2.5
Moonshot AI
Kimi K2.5 is a next-generation multimodal AI model designed for advanced reasoning, coding, and visual understanding tasks. It features a native multimodal architecture that supports both text and visual inputs, enabling image and video comprehension alongside natural language processing. Kimi K2.5 delivers open-source state-of-the-art performance in agent workflows, software development, and general intelligence tasks. The model offers ultra-long context support with a 256K token window, making it suitable for large documents and complex conversations. It includes long-thinking capabilities that allow multi-step reasoning and tool invocation for solving challenging problems. Kimi K2.5 is fully compatible with the OpenAI API format, allowing developers to switch seamlessly with minimal changes. With strong performance, flexibility, and developer-focused tooling, Kimi K2.5 is built for production-grade AI applications.Starting Price: Free -
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MiniMax M2.5
MiniMax
MiniMax M2.5 is a frontier AI model engineered for real-world productivity across coding, agentic workflows, search, and office tasks. Extensively trained with reinforcement learning in hundreds of thousands of real-world environments, it achieves state-of-the-art performance in benchmarks such as SWE-Bench Verified and BrowseComp. The model demonstrates strong architectural thinking, decomposing complex problems before generating code across more than ten programming languages. M2.5 operates at high throughput speeds of up to 100 tokens per second, enabling faster completion of multi-step tasks. It is optimized for efficient reasoning, reducing token usage and execution time compared to previous versions. With dramatically lower pricing than competing frontier models, it delivers powerful performance at minimal cost. Integrated into MiniMax Agent, M2.5 supports professional-grade office workflows, financial modeling, and autonomous task execution.Starting Price: Free -
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Qwen3-Coder-Next
Alibaba
Qwen3-Coder-Next is an open-weight language model specifically designed for coding agents and local development that delivers advanced coding reasoning, complex tool usage, and robust performance on long-horizon programming tasks with high efficiency, using a mixture-of-experts architecture that balances powerful capabilities with resource-friendly operation. It provides enhanced agentic coding abilities that help software developers, AI system builders, and automated coding workflows generate, debug, and reason about code with deep contextual understanding while recovering from execution errors, making it well-suited for autonomous coding agents and development-oriented applications. By achieving strong performance comparable to much larger parameter models while requiring fewer active parameters, Qwen3-Coder-Next enables cost-effective deployment for dynamic and complex programming workloads in research and production environments.Starting Price: Free -
28
GPT‑5-Codex
OpenAI
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-5.1-Codex-Max
OpenAI
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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GPT-5-Codex-Mini
OpenAI
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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GPT-5.1-Codex
OpenAI
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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CodeGen
Salesforce
CodeGen is an open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.Starting Price: Free -
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Codex Security
OpenAI
Codex Security is an AI-powered application security agent developed by OpenAI to help teams detect and fix vulnerabilities in software systems. The tool analyzes code repositories to understand the structure, architecture, and potential risk areas within a project. Using this context, it identifies complex security issues that traditional scanning tools might overlook. Codex Security prioritizes vulnerabilities based on their real-world impact, helping security teams focus on the most critical threats. The system also validates findings through sandboxed testing environments to reduce false positives and improve accuracy. Once vulnerabilities are confirmed, it proposes patches and remediation steps that align with the system’s existing behavior. By combining AI reasoning with automated validation, Codex Security helps development teams ship more secure code faster. -
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OpenAI Codex
OpenAI
Codex is an AI-powered coding agent from OpenAI designed to help developers build, manage, and ship software more efficiently across the entire development lifecycle. It acts as an intelligent pair programmer that can understand codebases, generate features, and deliver production-ready pull requests. Codex can safely execute commands in sandboxed environments while assisting with debugging, refactoring, and testing. A key advancement is its computer use capability, allowing it to operate your computer by seeing, clicking, and typing across applications. This enables Codex to interact with tools that don’t have APIs, making it useful for tasks like frontend testing and app navigation. The platform also includes an in-app browser and integrations with various developer tools for a more unified workflow. Codex supports automation by handling ongoing tasks such as monitoring, issue triage, and follow-ups. -
35
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.Starting Price: Free -
36
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 -
37
Cosyra
Cosyra
Cosyra is a mobile-first cloud development environment that enables users to run AI-powered coding tools directly from their phone through a full Linux terminal. It allows developers to use tools such as Claude Code, Codex CLI, OpenCode, and Gemini CLI, all pre-installed and ready to run by simply adding an API key and opening the terminal. It provides an isolated Ubuntu container with essential development tools, including Node.js, Python, Git, tmux, and vim, along with 30 GB of persistent storage that contains data between sessions. Cosyra is designed to replicate the experience of working on a local machine, allowing users to build, test, and manage projects entirely from a mobile device. It supports workflows such as cloning repositories, reviewing pull requests, running tests, and deploying code, all within a persistent session that can hibernate and resume seamlessly.Starting Price: $29.99 per month -
38
Polyscope
Beyond Code
Polyscope is an agent-first development environment designed to orchestrate and run multiple AI coding agents in parallel, allowing developers to automate complex software engineering workflows. It works with advanced coding models such as Claude Code and OpenAI Codex, enabling users to launch several agents simultaneously while maintaining separate, isolated workspaces for each task. Each agent operates inside its own copy-on-write environment, which allows the system to safely experiment with different approaches, modify files, and test changes without affecting the original project. It enables developers to run dozens of AI agents concurrently to generate code, analyze repositories, perform debugging, or experiment with alternative solutions across the same codebase. Itis delivered as a native macOS tool designed for high-performance agent execution, giving engineers a centralized interface to observe agent progress and manage tasks.Starting Price: $99 per year -
39
JetBrains Air
JetBrains
Air is an agentic development environment created by JetBrains that allows developers to delegate coding tasks to multiple AI agents and manage them within a single, unified workspace. Instead of functioning as a simple chat-based assistant, it is designed as a full development environment where tools are built around AI agents, enabling users to guide, supervise, and refine their output more effectively. Developers can run several agents concurrently, each working on different tasks in isolated environments, which helps prevent conflicts and improves productivity when handling complex projects. It supports integration with multiple AI systems such as Claude, Gemini, Codex, and other coding agents, allowing flexible, model-agnostic workflows within the same interface. Users can define tasks with rich context by referencing specific files, commits, classes, or code elements, ensuring that the agents generate more accurate and relevant results based on the actual codebase.Starting Price: Free -
40
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. -
41
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 -
42
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.Starting Price: Free -
43
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.Starting Price: Free -
44
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) -
45
GPT-4.1 nano
OpenAI
GPT-4.1 nano is the smallest and most efficient version of OpenAI's GPT-4.1 model, optimized for low-latency, cost-effective AI processing. Despite its compact size, GPT-4.1 nano delivers strong performance with a 1 million token context window, making it ideal for applications like classification, autocompletion, and smaller-scale tasks that require fast responses. It provides a highly efficient solution for businesses and developers who need an AI model that balances speed, cost, and performance.Starting Price: $0.10 per 1M tokens (input) -
46
Hamster
Hamster
Hamster is an AI-first workspace designed to help developers and teams plan, structure, and execute projects by providing persistent context to AI coding agents across tools and workflows. It allows users to define a clear plan, brief, and context that can be injected into multiple AI development tools such as Claude, Codex, Gemini, Copilot, and others, ensuring that every agent operates with the same understanding of the project. Instead of relying on isolated prompts, Hamster centralizes instructions and project knowledge so agents can generate more accurate, consistent, and goal-aligned outputs throughout the development process. It works as a coordination layer for AI-driven building, enabling users to move their plans seamlessly between tools while maintaining continuity and reducing context loss. By supporting a wide range of AI coding environments, Hamster acts as a universal interface that connects different models and systems into a cohesive workflow.Starting Price: Free -
47
VideoDB
VideoDB
VideoDB is a modern backend for AI agents, giving them the ability to see, understand, and act on video and audio in real time. It sits between raw media streams and agent reasoning systems, turning continuous streams into structured, searchable context with playable evidence. Our unified See->Understand->Act workflow replaces a fragmented stack of FFmpeg, vector DBs, and transcription tools with a single, programmable media layer. Featuring "Indexes-as-code," we allow developers to extract meaning from spoken words and visual scenes with near-zero latency. VideoDB supports Python and Node.js SDKs and integrates seamlessly with Claude, Cursor, and Codex via the Model Context Protocol (MCP). Built on a streaming-first architecture, it ensures your agents observe the world continuously rather than just reading static files. Whether you are building an AI meeting copilot, camera intelligence, or automated media editing, VideoDB provides the perception layer you need.Starting Price: $20/month -
48
GPT-4.1 mini
OpenAI
GPT-4.1 mini is a compact version of OpenAI’s powerful GPT-4.1 model, designed to provide high performance while significantly reducing latency and cost. With a smaller size and optimized architecture, GPT-4.1 mini still delivers impressive results in tasks such as coding, instruction following, and long-context processing. It supports up to 1 million tokens of context, making it an efficient solution for applications that require fast responses without sacrificing accuracy or depth.Starting Price: $0.40 per 1M tokens (input) -
49
CodexBanana
Pompiliu Rotaru
CodexBanana is a notes taking app (code snippets manager, text snippets utility, cheat sheets organizer, professional text template solution) that is simple to use. The design is focused on usability rather than looking cool. The software is free to use. It is available for Windows as a stand-alone applications, which can also connect to internet to access shared articles.Starting Price: 0.00 -
50
Cerebras-GPT
Cerebras
State-of-the-art language models are extremely challenging to train; they require huge compute budgets, complex distributed compute techniques and deep ML expertise. As a result, few organizations train large language models (LLMs) from scratch. And increasingly those that have the resources and expertise are not open sourcing the results, marking a significant change from even a few months back. At Cerebras, we believe in fostering open access to the most advanced models. With this in mind, we are proud to announce the release to the open source community of Cerebras-GPT, a family of seven GPT models ranging from 111 million to 13 billion parameters. Trained using the Chinchilla formula, these models provide the highest accuracy for a given compute budget. Cerebras-GPT has faster training times, lower training costs, and consumes less energy than any publicly available model to date.Starting Price: Free
