Alternatives to Grok Code Fast 1
Compare Grok Code Fast 1 alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Grok Code Fast 1 in 2026. Compare features, ratings, user reviews, pricing, and more from Grok Code Fast 1 competitors and alternatives in order to make an informed decision for your business.
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JetBrains Junie
JetBrains
Junie is an AI-powered coding agent developed by JetBrains designed to enhance developer productivity by integrating directly into popular IDEs such as IntelliJ IDEA, PyCharm, and Android Studio. It supports developers by assisting with code completion, testing, and inspections, ensuring code quality and reducing debugging time. Junie adapts seamlessly to your workflow, providing plans for execution and collaborating on complex coding tasks through different modes like code mode and ask mode. It understands project structure and logic, helping to find efficient solutions and maintain clean, production-ready code. Users can rely on Junie to run tests and verify changes, keeping projects stable and reducing compilation errors. With real-world examples from developers creating games and apps, Junie proves to be a versatile and intelligent assistant for coding projects of various scopes. -
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BLACKBOX AI
BLACKBOX AI
BLACKBOX AI is an advanced AI-powered platform designed to accelerate coding, app development, and deep research tasks. It features an AI Coding Agent that supports real-time voice interaction, GPU acceleration, and remote parallel task execution. Users can convert Figma designs into functional code and transform images into web applications with minimal coding effort. The platform enables screen sharing within IDEs like VSCode and offers mobile access to coding agents. BLACKBOX AI also supports integration with GitHub repositories for streamlined remote workflows. Its capabilities extend to website design, app building with PDF context, and image generation and editing.Starting Price: Free -
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Grok 4.5
SpaceXAI
Grok 4.5 is SpaceXAI’s advanced AI model built for coding, agentic tasks, engineering work, and knowledge-intensive productivity. The model is trained on coding, science, engineering, and math data, with reinforcement learning focused on multi-step software engineering and technical workflows. It is designed to handle real-world development tasks such as debugging, Rust and C/C++ work, terminal tasks, long-running agentic rollouts, and end-to-end app creation from a single prompt. Grok 4.5 is also built for fast serving, token efficiency, and lower-cost execution, with pricing based on input and output token usage. Beyond coding, the model supports business productivity tasks in Grok Build, including Excel modeling, PowerPoint diagram creation, Word writing, and research-assisted office workflows. Available through Grok Build, Cursor, and the SpaceXAI API console, Grok 4.5 gives developers and teams a high-performance model for building software, automating work, and more.Starting Price: $2 per million input tokens -
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Kimi K3
Moonshot AI
Kimi K3 is Moonshot AI’s most capable model, built for frontier intelligence scenarios such as software engineering, knowledge work, deep reasoning, and multimodal understanding. The model has 2.8 trillion parameters and uses Kimi Delta Attention, a hybrid linear attention mechanism, along with Attention Residuals for long-context performance. Kimi K3 supports a 1 million token context window, making it useful for analyzing large codebases, long documents, complex knowledge bases, and multi-step workflows. It includes native visual understanding for images and videos, with support for structured message formats, base64 image input, uploaded video files, and multimodal reasoning. Developers can use Kimi K3 through an OpenAI-compatible API with support for streaming, structured JSON output, partial mode, custom tools, dynamic tool loading, and automatic context caching.Starting Price: $3 per 1M tokens (input) -
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Gemini 3.5 Flash
Google
Gemini 3.5 Flash is Google’s latest frontier AI model designed to combine advanced intelligence, high-speed performance, and agentic workflow execution for developers, enterprises, and everyday users. Built as part of the Gemini 3.5 family, the model excels at coding, long-horizon reasoning, multimodal understanding, and complex multi-step automation tasks while delivering significantly faster output speeds than many competing frontier models. Gemini 3.5 Flash powers AI agents capable of planning, executing, and managing workflows such as application development, codebase maintenance, data analysis, and financial document preparation through the Antigravity harness. The model also supports rich multimodal experiences by generating interactive graphics, dynamic web interfaces, animations, and advanced visual content. Gemini 3.5 Flash is integrated across Google products including the Gemini app, Google Search AI Mode, Google Antigravity, Google AI Studio, Android Studio, and more.Starting Price: $1.50 per 1M tokens (input) -
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Kimi K2.7 Code
Moonshot AI
Kimi K2.7 Code is an open-source, coding-focused agentic AI model developed by Moonshot AI for long-horizon software engineering tasks. It is designed to improve coding performance, agent workflows, and real-world development assistance compared with earlier Kimi K2 versions. The model supports a 256K context window, making it useful for working with large codebases, long technical documents, and complex multi-step programming tasks. Kimi K2.7 Code is available through Kimi Code and API access, with OpenAI- and Anthropic-compatible options for easier integration into developer workflows. It is also listed on Hugging Face and supports deployment through inference engines such as vLLM, SGLang, and KTransformers. With improved agentic capabilities, long-context support, and reduced thinking-token usage compared with K2.6, Kimi K2.7 Code gives developers a flexible open-source option for AI-assisted coding.Starting Price: Free -
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Laguna S 2.1
Poolside
Laguna S 2.1 is an open weight agentic coding model designed to pursue longer-horizon work and make effective use of reasoning. It uses a 118-billion-parameter Mixture-of-Experts architecture with 8 billion active parameters per token and supports a context window of up to one million tokens in both thinking and no-thinking modes. Its compact active size makes it suitable for complex work on local machines while remaining competitive with models many times larger on terminal, software-engineering, codebase-question-answering, and tool-use benchmarks. Laguna S 2.1 is built to keep working through difficult tasks with greater persistence, verification, and willingness to backtrack instead of declaring success too early. In demonstrated runs, it built and validated a browser rendering engine from an empty folder, optimized an agent harness for faster execution and substantially lower memory allocation, and completed extended mathematical research using the tools in its environment. -
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DeepSeek-V4-Pro
DeepSeek
DeepSeek-V4-Pro is a large-scale Mixture-of-Experts (MoE) language model designed for advanced reasoning, coding, and long-context understanding. It features 1.6 trillion total parameters with 49 billion activated parameters, enabling high performance while maintaining efficiency. The model supports an exceptionally large context window of up to one million tokens, allowing it to process extensive documents and workflows. It uses a hybrid attention architecture to optimize long-context performance and reduce computational cost. DeepSeek-V4-Pro is trained on over 32 trillion tokens, improving its knowledge and reasoning capabilities. It also includes advanced optimization techniques for stability and faster convergence during training. The model supports multiple reasoning modes, allowing users to balance speed and accuracy based on their needs. Overall, it provides a powerful open-source solution for complex AI tasks and large-scale applications.Starting Price: $0.435 per 1M tokens (input) -
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Nemotron 3 Ultra
NVIDIA
Nemotron 3 Nano is a compact, open large language model in NVIDIA’s Nemotron 3 family, designed for efficient agentic reasoning, conversational AI, and coding tasks. It uses a hybrid Mixture-of-Experts Mamba-Transformer architecture that activates only a small subset of parameters per token, enabling low-latency inference while maintaining strong accuracy and reasoning performance. It has approximately 31.6 billion total parameters with around 3.2 billion active (3.6 billion including embeddings), allowing it to achieve higher accuracy than previous Nemotron 2 Nano while using less computation per forward pass. Nemotron 3 Nano supports long-context processing of up to one million tokens, enabling it to handle large documents, multi-step workflows, and extended reasoning chains in a single pass. It is designed for high-throughput, real-time execution, excelling in multi-turn conversations, tool calling, and agent-based workflows where tasks require planning, reasoning, and more. -
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Inkling
Thinking Machines Lab
Inkling is an open-weights multimodal AI model from Thinking Machines designed as a customizable foundation model for developers, researchers, and enterprises. The model is a Mixture-of-Experts transformer with 975 billion total parameters, 41 billion active parameters, and support for context windows up to 1 million tokens. Inkling was trained from scratch on text, images, audio, and video, giving it native capabilities across reasoning, coding, agentic tool use, vision, audio, factuality, and instruction following. It is built with controllable thinking effort so users can balance performance, latency, and token efficiency for different workloads. The model is available for fine-tuning on Tinker, with playground access, API availability through ecosystem partners, and full weights published on Hugging Face. Built for customization, Inkling gives teams an open-weights base model for building domain-specific AI systems, multimodal agents, coding workflows, research tools, and more.Starting Price: Free -
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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. -
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Claude Opus 4.7
Anthropic
Claude Opus 4.7 is the latest Anthropic AI model release designed to significantly improve performance in advanced software engineering and complex problem-solving tasks. It builds upon the previous Opus 4.6 model by delivering stronger results on difficult coding challenges and long-running workflows. The model is known for its ability to follow instructions precisely and verify its own outputs for greater reliability. It also introduces enhanced multimodal capabilities, particularly in processing high-resolution images with improved accuracy. Opus 4.7 supports more detailed visual tasks such as analyzing dense screenshots and extracting data from complex diagrams. In professional settings, it produces higher-quality outputs including documents, presentations, and user interfaces. The model includes updated safety features that detect and block high-risk cybersecurity-related requests.Starting Price: $5 per million tokens (input) -
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Claude Sonnet 4
Anthropic
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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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. -
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Agent 3
Replit
Replit Agent 3 is the most autonomous, AI-powered builder yet for creating production-ready applications entirely through natural-language prompts. You describe the app or website idea, and Agent automatically handles everything: setting up the full-stack environment, designing interfaces, configuring databases, managing dependencies, and integrating authentication or third-party services like Stripe or OpenAI. It offers two development modes: a visual-first “Start with a design” option that generates a clickable prototype in just minutes before enabling full functionality, or a “Build the full app” mode that constructs a functioning application, including frontend, backend, and integrations, in around 10 minutes. Agent 3 also self-tests within a browser workflow, identifying bugs, fixing them, and rerunning tests in a continuous reflection loop that is up to 3x faster and 10x more cost-efficient than traditional testing models.Starting Price: $20 per month -
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Grok 4
SpaceXAI
Grok 4 is the latest AI model from Elon Musk’s xAI, marking a significant advancement in AI reasoning and natural language understanding. Developed on the Colossus supercomputer, Grok 4 supports multimodal inputs including text and images, with plans to add video capabilities soon. It features enhanced precision in language tasks and has demonstrated superior performance in scientific reasoning and visual problem-solving compared to other leading AI models. Designed for developers, researchers, and technical users, Grok 4 offers powerful tools for complex tasks. The model incorporates improved moderation to address previous concerns about biased or problematic outputs. Grok 4 represents a major leap forward in AI’s ability to understand and generate human-like responses. -
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Grok 4.1
SpaceXAI
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 4.1 Fast
SpaceXAI
Grok 4.1 Fast is an 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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Grok 4.20
SpaceXAI
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 4.3
SpaceXAI
Grok 4.3 is the latest iteration of xAI’s Grok model, designed to deliver improved reasoning, real-time information access, and advanced task automation. It builds on earlier Grok 4 models by enhancing performance in complex problem-solving, coding, and analytical workflows. The model is integrated with real-time web and X (formerly Twitter) data, allowing it to provide up-to-date insights and answers. Grok 4.3 supports multimodal capabilities, enabling it to work with text, images, and other data types. It operates within the SuperGrok Heavy tier, offering access to more powerful compute and advanced features. The model is designed to handle long-context tasks and multi-step reasoning with greater accuracy. It also supports tool use and integrations, enabling it to interact with external systems and automate workflows. Overall, Grok 4.3 is positioned as a high-performance AI assistant for real-time, data-driven tasks. -
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Grok Build
SpaceXAI
Grok Build is an AI-powered command-line development environment designed to help developers build, manage, and automate software projects more efficiently. The platform provides a fast and flicker-free CLI experience that supports planning, coding, reviewing, and coordinating tasks across multiple AI-powered agents. Grok Build can adapt to different workflows and user preferences through customizable skills and interface enhancements. Developers can use the platform to architect complex projects with plan viewers, subagents, and parallel task execution capabilities. The system also includes marketplaces that allow teams to share workflows, capabilities, and productivity tools across projects. Grok Build supports interactive coding assistance, interface refinement suggestions, and contextual prompts that help streamline development processes.Starting Price: Free -
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Gemini 2.5 Pro
Google
Gemini 2.5 Pro is an advanced AI model designed to handle complex tasks with enhanced reasoning and coding capabilities. Leading common benchmarks, it excels in math, science, and coding, demonstrating strong performance in tasks like web app creation and code transformation. Built on the Gemini 2.5 foundation, it features a 1 million token context window, enabling it to process vast datasets from various sources such as text, images, and code repositories. Available now in Google AI Studio, Gemini 2.5 Pro is optimized for more sophisticated applications and supports advanced users with improved performance for complex problem-solving.Starting Price: $19.99/month -
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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 Gemini Enterprise Agent Platform, 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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Composer 1
Cursor
Composer is Cursor’s custom-built agentic AI model optimized specifically for software engineering tasks and designed to power fast, interactive coding assistance directly within the Cursor IDE, a VS Code-derived editor enhanced with intelligent automation. It is a mixture-of-experts model trained with reinforcement learning (RL) on real-world coding problems across large codebases, so it can produce high-speed, context-aware responses, from code edits and planning to answers that understand project structure, tools, and conventions, with generation speeds roughly four times faster than similar models in benchmarks. Composer is specialized for development workflows, leveraging long-context understanding, semantic search, and limited tool access (like file editing and terminal commands) so it can solve complex engineering requests with efficient and practical outputs.Starting Price: $20 per month -
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Composer 1.5
Cursor
Composer 1.5 is the latest agentic coding model from Cursor that balances speed and intelligence for everyday code tasks by scaling reinforcement learning approximately 20x more than its predecessor, enabling stronger performance on real-world programming challenges. It’s designed as a “thinking model” that generates internal reasoning tokens to analyze a user’s codebase and plan next steps, responding quickly to simple problems and engaging deeper reasoning on complex ones, while remaining interactive and fast for daily development workflows. To handle long-running tasks, Composer 1.5 introduces self-summarization, allowing the model to compress and carry forward context when it reaches context limits, which helps maintain accuracy across varying input lengths. Internal benchmarks show it surpasses Composer 1 in coding tasks, especially on more difficult issues, making it more capable for interactive use within Cursor’s environment. -
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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.Starting Price: Free -
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Devstral Small 2
Mistral AI
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.Starting Price: Free -
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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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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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GLM-5.1
Zhipu AI
GLM-5.1 is the latest iteration of Z.ai’s GLM series, designed as a frontier-level, agent-oriented AI model optimized for coding, reasoning, and long-horizon workflows. It builds on the GLM-5 architecture, which uses a Mixture-of-Experts (MoE) design to deliver high performance while keeping inference costs efficient, and is part of a broader push toward open-weight, developer-accessible models. A core focus of GLM-5.1 is enabling agentic behavior, meaning it can plan, execute, and iterate across multi-step tasks rather than simply responding to single prompts. It is specifically designed to handle complex workflows such as debugging code, navigating repositories, and executing chained operations with sustained context. Compared to earlier models, GLM-5.1 improves reliability in long interactions, maintaining coherence across extended sessions and reducing breakdowns in multi-step reasoning.Starting Price: Free -
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GPT-5
OpenAI
GPT-5 is OpenAI’s most advanced AI model, delivering smarter, faster, and more useful responses across a wide range of topics including math, science, finance, and law. It features built-in thinking capabilities that allow it to provide expert-level answers and perform complex reasoning. GPT-5 can handle long context lengths and generate detailed outputs, making it ideal for coding, research, and creative writing. The model includes a ‘verbosity’ parameter for customizable response length and improved personality control. It integrates with business tools like Google Drive and SharePoint to provide context-aware answers while respecting security permissions. Available to everyone, GPT-5 empowers users to collaborate with an AI assistant that feels like a knowledgeable colleague.Starting Price: $1.25 per 1M tokens -
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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 mini
OpenAI
GPT-5 mini is a streamlined, faster, and more affordable variant of OpenAI’s GPT-5, optimized for well-defined tasks and precise prompts. It supports text and image inputs and delivers high-quality text outputs with a 400,000-token context window and up to 128,000 output tokens. This model excels at rapid response times, making it suitable for applications requiring fast, accurate language understanding without the full overhead of GPT-5. Pricing is cost-effective, with input tokens at $0.25 per million and output tokens at $2 per million, providing savings over the flagship model. GPT-5 mini supports advanced features like streaming, function calling, structured outputs, and fine-tuning, but does not support audio input or image generation. It integrates well with various API endpoints including chat completions, responses, and embeddings, making it versatile for many AI-powered tasks.Starting Price: $0.25 per 1M tokens -
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GPT-5.1
OpenAI
GPT-5.1 is the latest update in the GPT-5 series, designed to make ChatGPT dramatically smarter and more conversational. The release introduces two distinct model variants: GPT-5.1 Instant, which is described as the most-used model and is now warmer, better at following instructions, and more intelligent; and GPT-5.1 Thinking, which is the advanced reasoning engine that’s been tuned to be easier to understand, faster on straightforward tasks, and more persistent on complex ones. Users' queries are now routed automatically to the variant best-suited to the task. The update emphasizes not just improved raw intelligence but also enhanced communication style; the models are tuned to be more natural, enjoyable to talk to, and better aligned with user intents. The system card addendum notes that GPT-5.1 Instant uses “adaptive reasoning” that lets it decide when to think more deeply before responding, while GPT-5.1 Thinking adapts its thinking time accurately to the question at hand. -
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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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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. -
40
GPT-5.1 Instant
OpenAI
GPT-5.1 Instant is a high-performance AI model designed for everyday users that combines speed, responsiveness, and improved conversational warmth. The model uses adaptive reasoning to instantly select how much computation is required for a task, allowing it to deliver fast answers without sacrificing understanding. It emphasizes stronger instruction-following, enabling users to give precise directions and expect consistent compliance. The model also introduces richer personality controls so chat tone can be set to Default, Friendly, Professional, Candid, Quirky, or Efficient, with experiments in deeper voice modulation. Its core value is to make interactions feel more natural and less robotic while preserving high intelligence across writing, coding, analysis, and reasoning. GPT-5.1 Instant routes user requests automatically from the base interface, with the system choosing whether this variant or the deeper “Thinking” model is applied. -
41
GPT-5.1 Pro
OpenAI
GPT-5.1 Pro is the highest-performance version of the GPT-5.1 model family, designed for research-grade reasoning and advanced analytical workloads. It delivers deeper, more structured thinking, making it ideal for complex problem-solving across coding, science, finance, law, and technical research. Unlike the Instant and Thinking versions, GPT-5.1 Pro is built to maintain accuracy under heavy cognitive load, producing clearer logic and more reliable multi-step reasoning. Pro users also gain access to extended context windows, allowing significantly longer inputs and deeper information processing. While it supports the full range of ChatGPT features, GPT-5.1 Pro is optimized for precision, rigor, and high-stakes tasks. It is available exclusively to ChatGPT Pro and Business customers. -
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GPT-5.1 Thinking
OpenAI
GPT-5.1 Thinking is the advanced reasoning model variant in the GPT-5.1 series, designed to more precisely allocate “thinking time” based on prompt complexity, responding faster to simpler requests and spending more effort on difficult problems. On a representative task distribution, it is roughly twice as fast on the fastest tasks and twice as slow on the slowest compared with its predecessor. Its responses are crafted to be clearer, with less jargon and fewer undefined terms, making deep analytical work more accessible and understandable. The model dynamically adjusts its reasoning depth, achieving a better balance between speed and thoroughness, particularly when dealing with technical concepts or multi-step questions. By combining high reasoning capacity with improved clarity, GPT-5.1 Thinking offers a powerful tool for tackling complex tasks, such as detailed analysis, coding, research, or technical explanations, while reducing unnecessary latency for routine queries. -
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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‑Codex‑Spark
OpenAI
GPT-5.3-Codex-Spark is an ultra-fast coding model designed for real-time collaboration inside Codex. Built as a smaller version of GPT-5.3-Codex, it delivers over 1000 tokens per second when served on low-latency Cerebras hardware. The model is optimized for interactive coding tasks, enabling developers to make targeted edits and see results almost instantly. With a 128k context window, Codex-Spark supports substantial project context while maintaining speed. It focuses on lightweight, precise edits and does not automatically run tests unless prompted. Infrastructure upgrades such as persistent WebSocket connections significantly reduce latency across the full request-response pipeline. Released as a research preview for ChatGPT Pro users, Codex-Spark marks the first milestone in OpenAI’s partnership with Cerebras. -
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MAI-Code-1-Flash
Microsoft AI
MAI-Code-1-Flash is a Microsoft coding model built for fast, efficient assistance in everyday developer workflows. Built end-to-end by Microsoft using clean and appropriately licensed data, the model is rolling out to GitHub Copilot individual users in Visual Studio Code through the model picker and the default Auto picker. It is designed around the goal of delivering high-quality coding help with better efficiency, helping engineering teams write better code faster through a lightweight, agentic model integrated into GitHub Copilot and VS Code. MAI-Code-1-Flash was trained directly with GitHub Copilot production harnesses, allowing it to interact with surrounding tools and systems in real developer environments rather than being optimized only for static benchmarks. It supports agentic coding, strong instruction-following across single-turn and multi-turn scenarios, repository question answering, refactoring, telemetry-grounded tasks, and adaptive thinking. -
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Mistral Large 3
Mistral AI
Mistral Large 3 is a next-generation, open multimodal AI model built with a powerful sparse Mixture-of-Experts architecture featuring 41B active parameters out of 675B total. Designed from scratch on NVIDIA H200 GPUs, it delivers frontier-level reasoning, multilingual performance, and advanced image understanding while remaining fully open-weight under the Apache 2.0 license. The model achieves top-tier results on modern instruction benchmarks, positioning it among the strongest permissively licensed foundation models available today. With native support across vLLM, TensorRT-LLM, and major cloud providers, Mistral Large 3 offers exceptional accessibility and performance efficiency. Its design enables enterprise-grade customization, letting teams fine-tune or adapt the model for domain-specific workflows and proprietary applications. Mistral Large 3 represents a major advancement in open AI, offering frontier intelligence without sacrificing transparency or control.Starting Price: Free -
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MiMo-V2-Omni
Xiaomi Technology
MiMo-V2-Omni is an advanced multimodal AI model designed to handle a wide range of real-world tasks across text, code, and other data formats. It is built to support agentic workflows, enabling seamless execution of complex, multi-step processes. The model integrates strong reasoning, tool usage, and contextual understanding to deliver reliable outputs. With its ability to process diverse inputs, it enhances productivity across development, automation, and enterprise use cases. MiMo-V2-Omni focuses on delivering consistent performance in both general and specialized tasks. -
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MiMo-V2-Pro
Xiaomi Technology
Xiaomi MiMo-V2-Pro is a flagship AI foundation model designed to power real-world agentic workflows and complex task execution. It is built to function as the core intelligence behind agent systems, enabling orchestration of multi-step processes and production-level tasks. The model demonstrates strong capabilities in coding, tool usage, and search-based tasks, performing competitively on global benchmarks. With its large-scale architecture and extended context window, it can handle long and complex interactions efficiently. MiMo-V2-Pro is optimized for practical applications, delivering reliable performance across development, automation, and enterprise workflows.Starting Price: $1/million tokens -
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MiMo-V2.5
Xiaomi Technology
Xiaomi MiMo-V2.5 is an advanced open-source AI model designed to combine strong agentic capabilities with native multimodal understanding. It can process and reason across text, images, and audio within a single unified system. The model uses a sparse Mixture-of-Experts architecture with hundreds of billions of parameters for efficient performance. It supports an extended context window of up to one million tokens, enabling long and complex workflows. MiMo-V2.5 is built to handle tasks such as coding, reasoning, and multimodal analysis with high accuracy. It incorporates dedicated visual and audio encoders to enhance perception and cross-modal reasoning. The model demonstrates strong benchmark performance across coding, reasoning, and multimodal tasks. By combining multimodality, efficiency, and agentic intelligence, MiMo-V2.5 advances the capabilities of open-source AI systems.