Alternatives to Composer 1
Compare Composer 1 alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Composer 1 in 2026. Compare features, ratings, user reviews, pricing, and more from Composer 1 competitors and alternatives in order to make an informed decision for your business.
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1
Amp
Amp Code
Amp is a frontier coding agent built to give developers full access to the power of today’s leading AI models directly in their workflow. Available in the terminal and popular editors like VS Code, Cursor, Windsurf, JetBrains, and Neovim, Amp integrates seamlessly into existing development environments. It enables developers to delegate complex coding tasks, refactors, reviews, and explorations to intelligent agents that understand and operate across entire codebases. With support for advanced models such as Claude Opus, Gemini, and GPT-class models, Amp delivers fast, reliable, and highly agentic code generation. The platform is designed for real-world engineering work, handling multi-file changes, deep context, and iterative improvements. Amp helps developers move faster while maintaining confidence in code quality.Starting Price: Free -
2
Cursor
Cursor
Cursor is an advanced AI-powered IDE designed to make developers exponentially more productive. Built with deep codebase understanding and intelligent automation, it combines natural language interaction with precise, context-aware editing tools. Its Agent feature acts as a human-AI coding partner capable of planning and executing entire development workflows, while the Tab model delivers remarkably accurate autocompletion and targeted suggestions. Cursor seamlessly integrates across environments—from GitHub and Slack to the command line—ensuring AI assistance is available wherever you code. Supporting leading models like GPT-5, Claude Sonnet, Gemini Pro, and Grok Code, it gives developers full control over autonomy and model selection. Fast, intuitive, and built for serious builders, Cursor is redefining what an IDE can be.Starting Price: $20 per month -
3
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 -
4
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 -
5
PromptKit
PromptKit
Transform your project ideas into clear, structured documentation. Let AI coding assistants like Cursor and GitHub Copilot understand your vision and generate more precise, context-aware code.Starting Price: $19/month -
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HunyuanOCR
Tencent
Tencent Hunyuan is a large-scale, multimodal AI model family developed by Tencent that spans text, image, video, and 3D modalities, designed for general-purpose AI tasks like content generation, visual reasoning, and business automation. Its model lineup includes variants optimized for natural language understanding, multimodal vision-language comprehension (e.g., image & video understanding), text-to-image creation, video generation, and 3D content generation. Hunyuan models leverage a mixture-of-experts architecture and other innovations (like hybrid “mamba-transformer” designs) to deliver strong performance on reasoning, long-context understanding, cross-modal tasks, and efficient inference. For example, the vision-language model Hunyuan-Vision-1.5 supports “thinking-on-image”, enabling deep multimodal understanding and reasoning on images, video frames, diagrams, or spatial data. -
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Ai2 OLMoE
The Allen Institute for Artificial Intelligence
Ai2 OLMoE is a fully open source mixture-of-experts language model that is capable of running completely on-device, allowing you to try our model privately and securely. Our app is intended to help researchers better explore how to make on-device intelligence better and to enable developers to quickly prototype new AI experiences, all with no cloud connectivity required. OLMoE is a highly efficient mixture-of-experts version of the Ai2 OLMo family of models. Experience which real-world tasks state-of-the-art local models are capable of. Research how to improve small AI models. Test your own models locally using our open-source codebase. Integrate OLMoE into other iOS applications. The Ai2 OLMoE app provides privacy and security by operating completely on-device. Easily share the output of your conversations with friends or colleagues. The OLMoE model and the application code are fully open source.Starting Price: Free -
8
Xgen-small
Salesforce
Xgen-small is an enterprise-ready compact language model developed by Salesforce AI Research, designed to deliver long-context performance at a predictable, low cost. It combines domain-focused data curation, scalable pre-training, length extension, instruction fine-tuning, and reinforcement learning to meet the complex, high-volume inference demands of modern enterprises. Unlike traditional large models, Xgen-small offers efficient processing of extensive contexts, enabling the synthesis of information from internal documentation, code repositories, research reports, and real-time data streams. With sizes optimized at 4B and 9B parameters, it provides a strategic advantage by balancing cost efficiency, privacy safeguards, and long-context understanding, making it a sustainable and predictable solution for deploying Enterprise AI at scale. -
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Olmo 3
Ai2
Olmo 3 is a fully open model family spanning 7 billion and 32 billion parameter variants that delivers not only high-performing base, reasoning, instruction, and reinforcement-learning models, but also exposure of the entire model flow, including raw training data, intermediate checkpoints, training code, long-context support (65,536 token window), and provenance tooling. Starting with the Dolma 3 dataset (≈9 trillion tokens) and its disciplined mix of web text, scientific PDFs, code, and long-form documents, the pre-training, mid-training, and long-context phases shape the base models, which are then post-trained via supervised fine-tuning, direct preference optimisation, and RL with verifiable rewards to yield the Think and Instruct variants. The 32 B Think model is described as the strongest fully open reasoning model to date, competitively close to closed-weight peers in math, code, and complex reasoning.Starting Price: Free -
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Qwen3-Coder
Qwen
Qwen3‑Coder is an agentic code model available in multiple sizes, led by the 480B‑parameter Mixture‑of‑Experts variant (35B active) that natively supports 256K‑token contexts (extendable to 1M) and achieves state‑of‑the‑art results comparable to Claude Sonnet 4. Pre‑training on 7.5T tokens (70 % code) and synthetic data cleaned via Qwen2.5‑Coder optimized both coding proficiency and general abilities, while post‑training employs large‑scale, execution‑driven reinforcement learning, scaling test‑case generation for diverse coding challenges, and long‑horizon RL across 20,000 parallel environments to excel on multi‑turn software‑engineering benchmarks like SWE‑Bench Verified without test‑time scaling. Alongside the model, the open source Qwen Code CLI (forked from Gemini Code) unleashes Qwen3‑Coder in agentic workflows with customized prompts, function calling protocols, and seamless integration with Node.js, OpenAI SDKs, and environment variables.Starting Price: Free -
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Yi-Lightning
Yi-Lightning
Yi-Lightning, developed by 01.AI under the leadership of Kai-Fu Lee, represents the latest advancement in large language models with a focus on high performance and cost-efficiency. It boasts a maximum context length of 16K tokens and is priced at $0.14 per million tokens for both input and output, making it remarkably competitive. Yi-Lightning leverages an enhanced Mixture-of-Experts (MoE) architecture, incorporating fine-grained expert segmentation and advanced routing strategies, which contribute to its efficiency in training and inference. This model has excelled in various domains, achieving top rankings in categories like Chinese, math, coding, and hard prompts on the chatbot arena, where it secured the 6th position overall and 9th in style control. Its development included comprehensive pre-training, supervised fine-tuning, and reinforcement learning from human feedback, ensuring both performance and safety, with optimizations in memory usage and inference speed. -
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MiniMax M1
MiniMax
MiniMax‑M1 is a large‑scale hybrid‑attention reasoning model released by MiniMax AI under the Apache 2.0 license. It supports an unprecedented 1 million‑token context window and up to 80,000-token outputs, enabling extended reasoning across long documents. Trained using large‑scale reinforcement learning with a novel CISPO algorithm, MiniMax‑M1 completed full training on 512 H800 GPUs in about three weeks. It achieves state‑of‑the‑art performance on benchmarks in mathematics, coding, software engineering, tool usage, and long‑context understanding, matching or outperforming leading models. Two model variants are available (40K and 80K thinking budgets), with weights and deployment scripts provided via GitHub and Hugging Face. -
13
GPT-4.1
OpenAI
GPT-4.1 is an advanced AI model from OpenAI, designed to enhance performance across key tasks such as coding, instruction following, and long-context comprehension. With a large context window of up to 1 million tokens, GPT-4.1 can process and understand extensive datasets, making it ideal for tasks like software development, document analysis, and AI agent workflows. Available through the API, GPT-4.1 offers significant improvements over previous models, excelling at real-world applications where efficiency and accuracy are crucial.Starting Price: $2 per 1M tokens (input) -
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PlayerZero
PlayerZero
PlayerZero is an AI-driven predictive software quality platform designed to help engineering, QA, and support teams monitor, diagnose, and resolve software issues before they impact customers by deeply understanding complex codebases and simulating how code will behave in real-world conditions. It applies proprietary AI models and semantic graph analysis to integrate signals from source code, runtime telemetry, customer tickets, documentation, and historical data, giving users unified, context-rich insights into what their software does, why it’s broken, and how to fix or improve it. Its agentic debugging agents can autonomously triage, root cause analyze, and even suggest fixes for issues, reducing escalations and accelerating resolution times while preserving audit trails, governance, and approval workflows. PlayerZero also includes CodeSim, an agentic code simulation capability powered by the Sim-1 model that predicts the impact of changes. -
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Qwen2.5-Max
Alibaba
Qwen2.5-Max is a large-scale Mixture-of-Experts (MoE) model developed by the Qwen team, pretrained on over 20 trillion tokens and further refined through Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). In evaluations, it outperforms models like DeepSeek V3 in benchmarks such as Arena-Hard, LiveBench, LiveCodeBench, and GPQA-Diamond, while also demonstrating competitive results in other assessments, including MMLU-Pro. Qwen2.5-Max is accessible via API through Alibaba Cloud and can be explored interactively on Qwen Chat.Starting Price: Free -
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MiMo-V2-Flash
Xiaomi Technology
MiMo-V2-Flash is an open weight large language model developed by Xiaomi based on a Mixture-of-Experts (MoE) architecture that blends high performance with inference efficiency. It has 309 billion total parameters but activates only 15 billion active parameters per inference, letting it balance reasoning quality and computational efficiency while supporting extremely long context handling, for tasks like long-document understanding, code generation, and multi-step agent workflows. It incorporates a hybrid attention mechanism that interleaves sliding-window and global attention layers to reduce memory usage and maintain long-range comprehension, and it uses a Multi-Token Prediction (MTP) design that accelerates inference by processing batches of tokens in parallel. MiMo-V2-Flash delivers very fast generation speeds (up to ~150 tokens/second) and is optimized for agentic applications requiring sustained reasoning and multi-turn interactions.Starting Price: Free -
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Qwen2
Alibaba
Qwen2 is the large language model series developed by Qwen team, Alibaba Cloud. Qwen2 is a series of large language models developed by the Qwen team at Alibaba Cloud. It includes both base language models and instruction-tuned models, ranging from 0.5 billion to 72 billion parameters, and features both dense models and a Mixture-of-Experts model. The Qwen2 series is designed to surpass most previous open-weight models, including its predecessor Qwen1.5, and to compete with proprietary models across a broad spectrum of benchmarks in language understanding, generation, multilingual capabilities, coding, mathematics, and reasoning.Starting Price: Free -
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Pencil
Pencil
Pencil.dev is an AI-powered design-in-code canvas and creative tool that brings visual interface design directly into development environments like Cursor, VS Code, and other IDEs so designers and engineers can work without handoffs between tools. Built around an agent-driven MCP (Model Context Protocol) canvas and an open design format that lives in your codebase, Pencil lets you draw, iterate, and generate pixel-perfect UI screens with AI assistance while keeping the design files versioned in Git alongside your source code, enabling branches, merges, and rollbacks like regular code. It eliminates the friction of switching between tools by embedding a Figma-like canvas into the IDE, supports importing frames and assets from Figma with vectors and styles intact, and lets you manipulate design elements directly with familiar editing panels, layers, and CSS-like properties, while AI models help generate screens, flows, and components in parallel.Starting Price: Free -
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GLM-4.5
Z.ai
GLM‑4.5 is Z.ai’s latest flagship model in the GLM family, engineered with 355 billion total parameters (32 billion active) and a companion GLM‑4.5‑Air variant (106 billion total, 12 billion active) to unify advanced reasoning, coding, and agentic capabilities in one architecture. It operates in a “thinking” mode for complex, multi‑step reasoning and tool use, and a “non‑thinking” mode for instant responses, supporting up to 128 K token context length and native function calling. Available via the Z.ai chat platform and API, with open weights on HuggingFace and ModelScope, GLM‑4.5 ingests diverse inputs to solve general problem‑solving, common‑sense reasoning, coding from scratch or within existing projects, and end‑to‑end agent workflows such as web browsing and slide generation. Built on a Mixture‑of‑Experts design with loss‑free balance routing, grouped‑query attention, and an MTP layer for speculative decoding, it delivers enterprise‑grade performance. -
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Kimi K2
Moonshot AI
Kimi K2 is a state-of-the-art open source large language model series built on a mixture-of-experts (MoE) architecture, featuring 1 trillion total parameters and 32 billion activated parameters for task-specific efficiency. Trained with the Muon optimizer on over 15.5 trillion tokens and stabilized by MuonClip’s attention-logit clamping, it delivers exceptional performance in frontier knowledge, reasoning, mathematics, coding, and general agentic workflows. Moonshot AI provides two variants, Kimi-K2-Base for research-level fine-tuning and Kimi-K2-Instruct pre-trained for immediate chat and tool-driven interactions, enabling both custom development and drop-in agentic capabilities. Benchmarks show it outperforms leading open source peers and rivals top proprietary models in coding tasks and complex task breakdowns, while its 128 K-token context length, tool-calling API compatibility, and support for industry-standard inference engines.Starting Price: Free -
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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). -
22
Kakoune
Kakoune
Kakoune is a highly efficient, modal text editor that focuses on real-time feedback and powerful, intuitive multi-selection capabilities. Inspired by Vim but offering its own distinct approach to modal editing, Kakoune prioritizes a selection-based workflow that makes text manipulation feel natural and fluid. Instead of commands operating on cursors, commands operate on selections, allowing users to edit and navigate with precision and speed. Kakoune features robust multi-caret editing, context-aware autocompletion, and extensive language support, with performance optimized for working with large files and complex codebases. Designed to be scriptable and extendable with shell commands, Kakoune integrates smoothly with UNIX tools, giving users flexibility in customization. Known for its responsiveness and adaptability, Kakoune is ideal for developers who prefer a keyboard-driven interface and appreciate real-time, immediate feedback in their editing workflow.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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DeepSeek-V2
DeepSeek
DeepSeek-V2 is a state-of-the-art Mixture-of-Experts (MoE) language model introduced by DeepSeek-AI, characterized by its economical training and efficient inference capabilities. With a total of 236 billion parameters, of which only 21 billion are active per token, it supports a context length of up to 128K tokens. DeepSeek-V2 employs innovative architectures like Multi-head Latent Attention (MLA) for efficient inference by compressing the Key-Value (KV) cache and DeepSeekMoE for cost-effective training through sparse computation. This model significantly outperforms its predecessor, DeepSeek 67B, by saving 42.5% in training costs, reducing the KV cache by 93.3%, and enhancing generation throughput by 5.76 times. Pretrained on an 8.1 trillion token corpus, DeepSeek-V2 excels in language understanding, coding, and reasoning tasks, making it a top-tier performer among open-source models.Starting Price: Free -
25
Double
Double
Double is an AI-powered coding assistant inside of VSCode, designed to generate high quality code and assist you with programming tasks. Double is powered by the most capable commercially available LLMs, providing state of the art coding assistance. We will never waste your precious time with inferior models. Get code suggestions in real time as you type in the editor, press Tab to accept a suggestion and incorporate it into your code. The suggestions are personalized to your file's context and style conventions. Double's autocomplete is also handles multi-cursor mode, naming variables, mid-line completions, and automatically imports any relevant functions, variables, and libraries needed to run the code.Starting Price: Free -
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DeepCoder
Agentica Project
DeepCoder is a fully open source code-reasoning and generation model released by Agentica Project in collaboration with Together AI. It is fine-tuned from DeepSeek-R1-Distilled-Qwen-14B using distributed reinforcement learning, achieving a 60.6% accuracy on LiveCodeBench (representing an 8% improvement over the base), a performance level that matches that of proprietary models such as o3-mini (2025-01-031 Low) and o1 while using only 14 billion parameters. It was trained over 2.5 weeks on 32 H100 GPUs with a curated dataset of roughly 24,000 coding problems drawn from verified sources (including TACO-Verified, PrimeIntellect SYNTHETIC-1, and LiveCodeBench submissions), each problem requiring a verifiable solution and at least five unit tests to ensure reliability for RL training. To handle long-range context, DeepCoder employs techniques such as iterative context lengthening and overlong filtering.Starting Price: Free -
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Monica Code
Monica
One-stop AI Coding Assistant for favorite code editor. Supports GPT-4o and Claude 3.5 Sonnet. Realtime code suggestion based on cursor location and comments while you coding. Select any code and update them with a simple prompt. Easily modify a function or rewrite the whole class. Chat with active file or whole indexed codebase using best models like Claude 3.5 Sonnet or GPT-4o, or send a screenshot to help debugging. Simply ask Monica Code to create or modify multiple files, and navigate through different composed versions. By describing your requirements in natural language, Monica Code can assist in generating appropriate code snippets or structure in your chosen language. This AI-assisted capability applies to various programming tasks, from simple scripts to more complex application structures.Starting Price: $16.60 per month -
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Llama 4 Scout
Meta
Llama 4 Scout is a powerful 17 billion active parameter multimodal AI model that excels in both text and image processing. With an industry-leading context length of 10 million tokens, it outperforms its predecessors, including Llama 3, in tasks such as multi-document summarization and parsing large codebases. Llama 4 Scout is designed to handle complex reasoning tasks while maintaining high efficiency, making it perfect for use cases requiring long-context comprehension and image grounding. It offers cutting-edge performance in image-related tasks and is particularly well-suited for applications requiring both text and visual understanding.Starting Price: Free -
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UIsnapper
UIsnapper
UIsnapper is an AI-powered tool that transforms UI screenshots into detailed prompts compatible with AI development environments like Cursor and Lovable. By uploading a screenshot, users receive structured, context-aware prompts that facilitate the rapid recreation of websites and applications without the need for manual coding. This streamlines the frontend development process, allowing developers to prototype and build interfaces more efficiently. UIsnapper is particularly beneficial for developers and designers aiming to accelerate their workflow by leveraging AI to convert visual designs into functional code.Starting Price: $5 per month -
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Mixtral 8x22B
Mistral AI
Mixtral 8x22B is our latest open model. It sets a new standard for performance and efficiency within the AI community. It is a sparse Mixture-of-Experts (SMoE) model that uses only 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. It is fluent in English, French, Italian, German, and Spanish. It has strong mathematics and coding capabilities. It is natively capable of function calling; along with the constrained output mode implemented on la Plateforme, this enables application development and tech stack modernization at scale. Its 64K tokens context window allows precise information recall from large documents. We build models that offer unmatched cost efficiency for their respective sizes, delivering the best performance-to-cost ratio within models provided by the community. Mixtral 8x22B is a natural continuation of our open model family. Its sparse activation patterns make it faster than any dense 70B model.Starting Price: Free -
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BrainGrid
BrainGrid
BrainGrid is an AI-powered software planning and requirements platform that helps developers turn rough ideas and high-level thoughts into engineering-ready specifications, structured tasks, and precise prompts so AI coding agents (such as Cursor, Claude Code, Replit, and others) can build reliable software instead of fragile prototypes. It starts by deeply analyzing your existing codebase, including architecture, data models, and dependencies, and then works interactively with you to clarify scope, ask the right questions, and refine concept descriptions into detailed, code-aware requirements. BrainGrid breaks these requirements down into atomic, verifiable tasks with context, goals, dependencies, and acceptance criteria, generating prompts designed to keep AI coding tools on track and dramatically increase the probability of accurate, first-time execution. It also supports automatic task generation, continual improvement of specs, and integration with multiple AI coding workflows.Starting Price: $10 per month -
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DeepSeek R2
DeepSeek
DeepSeek R2 is the anticipated successor to DeepSeek R1, a groundbreaking AI reasoning model launched in January 2025 by the Chinese AI startup DeepSeek. Building on R1’s success, which disrupted the AI industry with its cost-effective performance rivaling top-tier models like OpenAI’s o1, R2 promises a quantum leap in capabilities. It is expected to deliver exceptional speed and human-like reasoning, excelling in complex tasks such as advanced coding and high-level mathematical problem-solving. Leveraging DeepSeek’s innovative Mixture-of-Experts architecture and efficient training methods, R2 aims to outperform its predecessor while maintaining a low computational footprint, potentially expanding its reasoning abilities to languages beyond English.Starting Price: Free -
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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) -
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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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Bito
Bito
Bito uses AI to streamline code reviews, making them faster and more consistent. The AI Code Review Agent understands the broader codebase and delivers precise, context-aware suggestions on pull requests. Engineering teams rely on Bito to speed up review cycles, catch regressions early, and improve code quality. It integrates with GitHub, GitLab, and Bitbucket, and installs with a single click. No code is stored, and no models are trained on your data.Starting Price: $15/seat/month -
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Amazon Nova 2 Lite
Amazon
Nova 2 Lite is a lightweight, high-speed reasoning model designed to handle everyday AI workloads across text, images, and video. It can generate clear, context-aware responses and lets users fine-tune how much internal reasoning the model performs before producing an answer. This adjustable “thinking depth” gives teams the flexibility to choose faster replies or more detailed problem-solving depending on the task. It stands out for customer service bots, automated document handling, and general business workflow support. Nova 2 Lite delivers strong performance across standard evaluation tests. It performs on par with or better than comparable compact models in most benchmark categories, demonstrating reliable comprehension and response quality. Its strengths include interpreting complex documents, pulling accurate insights from video content, generating usable code, and delivering grounded answers based on provided information. -
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Traycer
Traycer AI
Traycer transforms your ideas into clear, step-by-step plans that AI coding tools like Claude Code and Cursor can follow easily. Spend less time writing prompts and complete your projects faster. ✨ Detailed step by step implementation plans ✅ Perfect for large scale code refactoring and feature roll 🛠️ Seamless IDE integration (Copilot, Cursor, Windsurf, etc) 🤖 Powered by cutting-edge AI models like Sonnet 4, o3, GPT 4.1 and more 🎁 Free to use forever 🚀 14 day Pro trial, no credit card neededStarting Price: Free -
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MAI-1-preview
Microsoft
MAI-1 Preview is Microsoft AI’s first end-to-end trained foundation model, built entirely in-house as a mixture-of-experts architecture. Pre-trained and post-trained on approximately 15,000 NVIDIA H100 GPUs, it is designed to follow instructions and generate helpful, responsive text for everyday user queries, representing a prototype of future Copilot capabilities. Now available for public testing on LMArena, MAI-1 Preview delivers an early glimpse into the platform’s trajectory, with plans to roll out select text-based applications within Copilot over the coming weeks to gather user feedback and refine performance. Microsoft reinforces that it will continue combining its own models, partner models, and developments from the open-source community to flexibly power experiences across millions of unique interactions each day. -
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Gemini 2.5 Pro Deep Think
Google
Gemini 2.5 Pro Deep Think is a cutting-edge AI model designed to enhance the reasoning capabilities of machine learning models, offering improved performance and accuracy. This advanced version of the Gemini 2.5 series incorporates a feature called "Deep Think," allowing the model to reason through its thoughts before responding. It excels in coding, handling complex prompts, and multimodal tasks, offering smarter, more efficient execution. Whether for coding tasks, visual reasoning, or handling long-context input, Gemini 2.5 Pro Deep Think provides unparalleled performance. It also introduces features like native audio for more expressive conversations and optimizations that make it faster and more accurate than previous versions. -
40
GigaChat 3 Ultra
Sberbank
GigaChat 3 Ultra is a 702-billion-parameter Mixture-of-Experts model built from scratch to deliver frontier-level reasoning, multilingual capability, and deep Russian-language fluency. It activates just 36 billion parameters per token, enabling massive scale with practical inference speeds. The model was trained on a 14-trillion-token corpus combining natural, multilingual, and high-quality synthetic data to strengthen reasoning, math, coding, and linguistic performance. Unlike modified foreign checkpoints, GigaChat 3 Ultra is entirely original—giving developers full control, modern alignment, and a dataset free of inherited limitations. Its architecture leverages MoE, MTP, and MLA to match open-source ecosystems and integrate easily with popular inference and fine-tuning tools. With leading results on Russian benchmarks and competitive performance on global tasks, GigaChat 3 Ultra represents one of the largest and most capable open-source LLMs in the world.Starting Price: Free -
41
GPT-5.2 Pro
OpenAI
GPT-5.2 Pro is the highest-capability variant of OpenAI’s latest GPT-5.2 model family, built to deliver professional-grade reasoning, complex task performance, and enhanced accuracy for demanding knowledge work, creative problem-solving, and enterprise-level applications. It builds on the foundational improvements of GPT-5.2, including stronger general intelligence, superior long-context understanding, better factual grounding, and improved tool use, while using more compute and deeper processing to produce more thoughtful, reliable, and context-rich responses for users with intricate, multi-step requirements. GPT-5.2 Pro is designed to handle challenging workflows such as advanced coding and debugging, deep data analysis, research synthesis, extensive document comprehension, and complex project planning with greater precision and fewer errors than lighter variants. -
42
DeepSeek-Coder-V2
DeepSeek
DeepSeek-Coder-V2 is an open source code language model designed to excel in programming and mathematical reasoning tasks. It features a Mixture-of-Experts (MoE) architecture with 236 billion total parameters and 21 billion activated parameters per token, enabling efficient processing and high performance. The model was trained on an extensive dataset of 6 trillion tokens, enhancing its capabilities in code generation and mathematical problem-solving. DeepSeek-Coder-V2 supports over 300 programming languages and has demonstrated superior performance on benchmarks such surpassing other models. It is available in multiple variants, including DeepSeek-Coder-V2-Instruct, optimized for instruction-based tasks; DeepSeek-Coder-V2-Base, suitable for general text generation; and lightweight versions like DeepSeek-Coder-V2-Lite-Base and DeepSeek-Coder-V2-Lite-Instruct, designed for environments with limited computational resources. -
43
GLM-4.7-FlashX
Z.ai
GLM-4.7 FlashX is a lightweight, high-speed version of the GLM-4.7 large language model created by Z.ai that balances efficiency and performance for real-time AI tasks across English and Chinese while offering the core capabilities of the broader GLM-4.7 family in a more resource-friendly package. It is positioned alongside GLM-4.7 and GLM-4.7 Flash, delivering optimized agentic coding and general language understanding with faster response times and lower resource needs, making it suitable for applications that require rapid inference without heavy infrastructure. As part of the GLM-4.7 model series, it inherits the model’s strengths in programming, multi-step reasoning, and robust conversational understanding, and it supports long contexts for complex tasks while remaining lightweight enough for deployment with constrained compute budgets.Starting Price: $0.07 per 1M tokens -
44
doteval
doteval
doteval is an AI-assisted evaluation workspace that simplifies the creation of high-signal evaluations, alignment of LLM judges, and definition of rewards for reinforcement learning, all within a single platform. It offers a Cursor-like experience to edit evaluations-as-code against a YAML schema, enabling users to version evaluations across checkpoints, replace manual effort with AI-generated diffs, and compare evaluation runs on tight execution loops to align them with proprietary data. doteval supports the specification of fine-grained rubrics and aligned graders, facilitating rapid iteration and high-quality evaluation datasets. Users can confidently determine model upgrades or prompt improvements and export specifications for reinforcement learning training. It is designed to accelerate the evaluation and reward creation process by 10 to 100 times, making it a valuable tool for frontier AI teams benchmarking complex model tasks. -
45
DBRX
Databricks
Today, we are excited to introduce DBRX, an open, general-purpose LLM created by Databricks. Across a range of standard benchmarks, DBRX sets a new state-of-the-art for established open LLMs. Moreover, it provides the open community and enterprises building their own LLMs with capabilities that were previously limited to closed model APIs; according to our measurements, it surpasses GPT-3.5, and it is competitive with Gemini 1.0 Pro. It is an especially capable code model, surpassing specialized models like CodeLLaMA-70B in programming, in addition to its strength as a general-purpose LLM. This state-of-the-art quality comes with marked improvements in training and inference performance. DBRX advances the state-of-the-art in efficiency among open models thanks to its fine-grained mixture-of-experts (MoE) architecture. Inference is up to 2x faster than LLaMA2-70B, and DBRX is about 40% of the size of Grok-1 in terms of both total and active parameter counts. -
46
Xiaomi MiMo
Xiaomi Technology
The Xiaomi MiMo API open platform is a developer-oriented interface for accessing and integrating Xiaomi’s MiMo family of AI models, including reasoning and language models such as MiMo-V2-Flash, into applications and services through standardized APIs and cloud endpoints, enabling developers to build AI-enabled features like conversational agents, reasoning workflows, code assistance, and search-augmented tasks without managing model infrastructure themselves. It offers REST-style API access with authentication, request signing, and structured responses so software can send prompts and receive generated text or processed outputs programmatically, and it supports common operations like text generation, prompt handling, and inference over MiMo models. By providing documentation and onboarding tools, the open platform lets teams integrate Xiaomi’s latest open source large language models, which leverage Mixture-of-Experts (MoE) architectures.Starting Price: Free -
47
Grok 4.1 Fast
xAI
Grok 4.1 Fast is the newest xAI model designed to deliver advanced tool-calling capabilities with a massive 2-million-token context window. It excels at complex real-world tasks such as customer support, finance, troubleshooting, and dynamic agent workflows. The model pairs seamlessly with the new Agent Tools API, which enables real-time web search, X search, file retrieval, and secure code execution. This combination gives developers the power to build fully autonomous, production-grade agents that plan, reason, and use tools effectively. Grok 4.1 Fast is trained with long-horizon reinforcement learning, ensuring stable multi-turn accuracy even across extremely long prompts. With its speed, cost-efficiency, and high benchmark scores, it sets a new standard for scalable enterprise-grade AI agents. -
48
VideoPoet
Google
VideoPoet is a simple modeling method that can convert any autoregressive language model or large language model (LLM) into a high-quality video generator. It contains a few simple components. An autoregressive language model learns across video, image, audio, and text modalities to autoregressively predict the next video or audio token in the sequence. A mixture of multimodal generative learning objectives are introduced into the LLM training framework, including text-to-video, text-to-image, image-to-video, video frame continuation, video inpainting and outpainting, video stylization, and video-to-audio. Furthermore, such tasks can be composed together for additional zero-shot capabilities. This simple recipe shows that language models can synthesize and edit videos with a high degree of temporal consistency. -
49
LTM-2-mini
Magic AI
LTM-2-mini is a 100M token context model: LTM-2-mini. 100M tokens equals ~10 million lines of code or ~750 novels. For each decoded token, LTM-2-mini’s sequence-dimension algorithm is roughly 1000x cheaper than the attention mechanism in Llama 3.1 405B1 for a 100M token context window. The contrast in memory requirements is even larger – running Llama 3.1 405B with a 100M token context requires 638 H100s per user just to store a single 100M token KV cache.2 In contrast, LTM requires a small fraction of a single H100’s HBM per user for the same context. -
50
Chartboard
Ivyware Pty Ltd
Technical Analysis Workspace. Charting, Modelling and Portfolio management plus custom Python scripting for Advisor, Scanning and AI integration. Workspace state archived at shutdown and restored at startup. Diagnostic console and context sensitive cursor for Python script development and debugging. Extensive help and training provided via embedded context sensitive URL's and/or YouTube videos.Starting Price: $0
