Find and compare the best Artificial Intelligence software for Kilo Code in 2026
Sort:
Use the comparison tool below to compare the top Artificial Intelligence software for Kilo Code on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
-
1
Kilo Code Reviewer
Kilo Code
FreeKilo Code Reviewer is an innovative code review tool that utilizes AI to assess pull requests instantly upon their creation or modification, comprehending the context of the changes and delivering practical feedback through inline comments, detailed explanations, and suggestions aimed at identifying bugs, security vulnerabilities, performance issues, style inconsistencies, gaps in testing, and missing documentation prior to human evaluation. This tool boasts seamless integration with platforms like GitHub, GitLab, and is set to incorporate Bitbucket soon, allowing users to select from a variety of models while adjusting the rigor and focus of reviews to align with their team's coding standards. Moreover, it can be executed locally within popular IDEs such as VS Code or JetBrains, enabling developers to detect problems before they commit their code. The setup process is straightforward: simply link a repository, choose an AI model and review parameters, and the system automatically begins monitoring pull requests, thereby ensuring consistent adherence to coding guidelines and providing immediate, context-sensitive insights that enhance the capabilities of human reviewers. As a result, Kilo Code Reviewer not only streamlines the review process but also significantly improves code quality and team productivity. -
2
MiniMax M2.5
MiniMax
FreeMiniMax M2.5 is a next-generation foundation model built to power complex, economically valuable tasks with speed and cost efficiency. Trained using large-scale reinforcement learning across hundreds of thousands of real-world task environments, it excels in coding, tool use, search, and professional office workflows. In programming benchmarks such as SWE-Bench Verified and Multi-SWE-Bench, M2.5 reaches state-of-the-art levels while demonstrating improved multilingual coding performance. The model exhibits architect-level reasoning, planning system structure and feature decomposition before writing code. With throughput speeds of up to 100 tokens per second, it completes complex evaluations significantly faster than earlier versions. Reinforcement learning optimizations enable more precise search rounds and fewer reasoning steps, improving overall efficiency. M2.5 is available in two variants—standard and Lightning—offering identical capabilities with different speed configurations. Pricing is designed to be dramatically lower than competing frontier models, reducing cost barriers for large-scale agent deployment. Integrated into MiniMax Agent, the model supports advanced office skills including Word formatting, Excel financial modeling, and PowerPoint editing. By combining high performance, efficiency, and affordability, MiniMax M2.5 aims to make agent-powered productivity accessible at scale. -
3
MiniMax M2.7
MiniMax
FreeMiniMax M2.7 is a powerful AI model built to drive real-world productivity across coding, search, and office-based workflows. It is trained using reinforcement learning across a wide range of real-world environments, enabling it to execute complex, multi-step tasks with precision and efficiency. The model demonstrates strong problem-solving capabilities by breaking down challenges into structured steps before generating solutions across multiple programming languages. It delivers high-speed performance with rapid token output, ensuring faster completion of demanding tasks. With optimized reasoning, it reduces token usage and execution time, making it more efficient than previous models. M2.7 also achieves state-of-the-art results in software engineering benchmarks, significantly improving response times for technical issues. Its advanced agentic capabilities allow it to work seamlessly with tools and support complex workflows with high skill accuracy. The model is designed to handle professional tasks, including multi-turn interactions and high-quality document editing. It also provides strong support for office productivity, enabling efficient handling of structured data and business tasks. With competitive pricing, it delivers high performance while remaining cost-effective. Overall, it combines speed, intelligence, and versatility to meet the needs of modern professionals and teams. -
4
MiMo-V2-Pro
Xiaomi Technology
$1/million tokens Xiaomi MiMo-V2-Pro is an advanced AI foundation model engineered to support real-world agentic workloads and complex workflow orchestration. It serves as the central intelligence for agent systems, enabling seamless coordination of coding, search, and multi-step task execution. The model is built on a large-scale architecture with over a trillion parameters, supporting extended context lengths for handling complex scenarios. It demonstrates strong benchmark performance, particularly in coding and agent-based evaluations, placing it among top-tier global models. MiMo-V2-Pro is optimized for real-world usability, focusing on reliability, efficiency, and practical task completion rather than just theoretical performance. It features improved tool-calling accuracy and stability, making it suitable for integration into production environments. The model also excels in software engineering tasks, offering structured reasoning and high-quality code generation. With its ability to handle long-context interactions, it supports advanced workflows across development and automation use cases. Its API accessibility and competitive pricing make it attractive for developers and enterprises. Overall, MiMo-V2-Pro delivers a balance of scale, intelligence, and real-world performance for modern AI applications. -
5
KiloClaw
Kilo Code
$4 per monthKiloClaw offers a comprehensive cloud-hosted solution for the open source AI agent OpenClaw, enabling users to easily deploy and operate a robust autonomous AI assistant without the complexities of infrastructure management, setup, or ongoing maintenance. With a streamlined one-click deployment process, individuals can have a functional AI agent up and running in less than a minute, removing barriers like Docker, server management, SSH configuration, or any manual environment preparations. Operating on Kilo’s advanced infrastructure, it connects seamlessly to over 500 AI models through the Kilo Gateway, giving users the flexibility to switch models or integrate their own API keys while ensuring a consistent billing and management experience. KiloClaw agents excel in executing real-world tasks beyond mere text generation, such as browsing the internet, executing commands, organizing files, scheduling activities, and engaging across various chat platforms like Telegram, Discord, and Slack. This capability makes it a versatile tool for both personal and professional use, providing a significant efficiency boost in task management. -
6
OpenSpec
Fission AI
FreeOpenSpec is an open-source framework designed to enhance AI-assisted development through a structured, spec-driven approach. It provides a system for defining requirements before coding, ensuring alignment between developers and AI tools. The platform organizes work into clear artifacts, including proposals, specifications, design documents, and task checklists. It integrates with more than 20 AI coding assistants, making it compatible with a wide range of tools and workflows. OpenSpec promotes an iterative and flexible process, allowing teams to refine specifications as projects evolve. Its command-based interface enables users to propose features, implement changes, and archive completed work efficiently. By introducing structure, it reduces the unpredictability often associated with AI-generated code. The framework supports both individual developers and large teams, scaling across different project sizes. It also emphasizes context management to improve the accuracy and relevance of AI outputs. Ultimately, OpenSpec helps teams build software more reliably by combining human intent with AI execution in a structured workflow. -
7
Mercury Edit 2
Inception
$0.25 per 1M input tokensMercury Edit 2 is a cutting-edge AI model from Inception Labs, part of the Mercury suite, specifically crafted for rapid reasoning, coding, and editing by employing a novel architecture distinctly different from typical large language models. It enhances the capabilities of Mercury 2, a diffusion-based model that generates and refines complete outputs simultaneously, rather than the conventional method of creating text one token at a time, which results in markedly improved speeds and more agile editing processes. Rather than functioning as a linear “typewriter,” this system operates as a dynamic editor, beginning with a rough draft and methodically enhancing it across multiple tokens simultaneously, facilitating real-time engagement and swift iterations in various tasks such as code editing, content creation, and agent-based workflows. This innovative framework achieves an impressive throughput of up to approximately 1,000 tokens per second, significantly outpacing traditional models while still upholding competitive reasoning abilities across various benchmarks. Its unique design not only transforms the way users interact with AI but also sets a new standard for performance in the field of artificial intelligence. -
8
Constellation
ShiftinBits Inc
$29.99/month Your AI agents lack a true comprehension of your codebase; it's time to transition from mere text searching to genuine code understanding. Traditional AI coding agents often squander their context window on searching through files and making assumptions about the structure of the code. With Constellation, you can provide them with a comprehensive, team-wide knowledge graph of your codebase, which includes features like symbol search, dependency graphs, and impact analysis, all accessed through MCP. This innovative approach ensures that every token is utilized for reasoning rather than for the discovery process, leading to greater efficiency and more accurate code comprehension. By enhancing the understanding of the code, your team can work more cohesively and effectively. -
9
Laguna XS.2
Poolside
FreeLaguna XS.2 represents Poolside’s innovative open-weight coding model, distinguished as the lightest and quickest member of the Laguna series. This model features a total of 33 billion parameters in a Mixture of Experts setup, with 3 billion parameters activated, and has been meticulously trained in-house using 30 trillion tokens. As the latest generation model accessible to the public, it embodies a second-generation architecture and marks Poolside’s inaugural open-weight offering, drawing from insights gained during the training of Laguna M.1 with synthetic data and reinforcement learning techniques. Specifically designed to enhance agentic coding workflows, Laguna XS.2 excels in coding, acting, and rapidly iterating, particularly within Poolside’s coding agent environment. This model is particularly advantageous for developers and teams seeking a lightweight, efficient coding solution rather than a more cumbersome frontier system. Released under the permissive Apache 2.0 license, it empowers the community to assess, fine-tune, quantize, and build upon its weights, fostering a collaborative development atmosphere. In essence, Laguna XS.2 not only provides a robust platform for agentic coding but also encourages innovation and experimentation among its users. -
10
Laguna M.1
Poolside
FreeLaguna M.1 stands out as Poolside's most proficient model for agentic coding, meticulously developed in-house specifically for enhancing software development workflows. This model features a total of 225 billion parameters, utilizing a Mixture of Experts architecture with 23 billion activated parameters, and has been trained entirely within the organization on a dataset consisting of 30 trillion tokens, leveraging the power of 6,144 interconnected NVIDIA H200 GPUs. Poolside undertook the task of training Laguna M.1 from the ground up, employing its proprietary data, dedicated training codebase, and an asynchronous on-policy reinforcement learning approach within its agent framework, all tailored for agentic coding applications. The design of the model ensures optimal performance within Poolside's coding agent, enabling it to effectively reason through software tasks, interact with various tools, edit code, execute tests, and facilitate extended autonomous development sessions. Specifically crafted for developers and teams tackling intricate coding challenges, Laguna M.1 offers enhanced capabilities in reasoning, architectural comprehension, terminal operations, and multi-step execution, surpassing what lighter models can achieve. Ultimately, its robust feature set positions it as an essential asset for those engaged in demanding software projects. -
11
Ling 2.6
Ant Group
$0.0028 per 1M tokensLing 2.6 represents an independently developed and open-source series of large language models created by Ant Group, utilizing a Mixture of Experts (MoE) architecture to enhance inference efficiency, long context modeling, training methodologies, and collaborative reasoning for AI agents. By employing this MoE architecture, Ling effectively directs each token to engage only the most pertinent expert subnetworks, significantly reducing the computational load while preserving the extensive capabilities of the model. This series makes strides in long-sequence modeling, exemplified by Ling-2.6-1T, which accommodates a native context window of up to 1 million tokens and offers a 256K context window through its official API; additionally, Ling-2.6-flash features a native 256K context window, enabling it to handle around 200,000 characters in lengthy inputs. These models are meticulously crafted to ensure dependable retrieval of long-range information without any discernible loss of quality, regardless of whether the data is located at the start, middle, or end of the context. This innovative approach to long-context processing sets a new benchmark for efficiency and reliability in language model performance. -
12
Ling 2.6 Flash
Ant Group
$0.00037 per 1M tokensThe Ling 2.6 Flash represents the newest and most economical addition to the Ling series, utilizing a Mixture of Experts architecture that encompasses a total of 104 billion parameters, with 7.4 billion of those being actively engaged. This model is crafted to strike an ideal balance between inference speed and computational expense, making it an excellent fit for diverse scenarios where reasoning prowess, high throughput, and effective deployment are essential. By employing its MoE structure, Ling ensures that each token activates only the most pertinent expert subnetworks, significantly reducing the actual computational load while preserving the expansive capacity of the model. Offering a native context window of 256K, Ling 2.6 Flash is capable of handling around 200,000 characters of lengthy input, adeptly retrieving critical long-range information regardless of its position in the context. Furthermore, its overall benchmark performance rivals or surpasses that of 40 billion parameter Dense models, highlighting its competitive edge in the field of AI. This blend of efficiency and performance makes Ling 2.6 Flash a noteworthy option for developers seeking advanced capabilities without excessive resource demands. -
13
Ring 2.6
Ant Group
$0.0028 per 1M tokensRing is a sophisticated trillion-parameter thinking model created by Ant Group, specifically tailored for real-world Agent workflows. It employs a Mixture of Experts architecture similar to that of Ling, activating approximately 63 billion parameters during each inference, and is particularly geared towards tasks such as coding agents, utilizing tools, collaborating with multiple tools, engineering development, conducting research analysis, and executing long-term tasks. Instead of merely striving for "smarter" outcomes, Ring prioritizes the reliable completion of intricate tasks while maintaining a cost-effective approach, effectively balancing quality, speed, and efficiency in production settings. The latest iteration, Ring-2.6-1T, incorporates an adjustable Reasoning Effort mechanism that features high and xhigh reasoning intensity levels, which allocates an adaptive reasoning budget according to the complexity of the task at hand. The high mode is specifically optimized for high-frequency Agent workflows, resulting in lower token costs and quicker multi-step execution, while also facilitating multi-turn interactions, tool collaboration, and task decomposition. As a result, Ring demonstrates a significant advancement in enhancing the capabilities of agents in various operational contexts. -
14
Tencent Hy
Tencent
Tencent HY is a versatile and comprehensive family of large models developed in-house by Tencent, designed to deliver AI solutions tailored for enterprise needs across various domains such as content creation, business automation, and real-world agent functionalities. It encompasses multiple modalities, including language, imagery, 3D modeling, and translation, seamlessly integrating Tencent’s proprietary algorithms with advanced natural language processing and computer vision technologies to enable superior image generation, 3D content creation, and intelligent applications. Via Tencent Hunyuan AI Studio, users can engage with the model through intuitive human-computer dialogue, which allows the system to comprehend commands, perform tasks, assist users in information retrieval, generate content, and discover the model's extensive capabilities in a user-friendly environment. Additionally, Tencent HY facilitates API integration and customizable parameter configurations, enhancing accessibility and usability for developers, product teams, and enterprise-focused applications. This adaptability ensures that a wide range of users can leverage the power of Tencent HY in their projects, driving innovation and efficiency across industries. -
15
MiMo-V2.5-Pro
Xiaomi Technology
Xiaomi MiMo-V2.5-Pro is a next-generation open-source AI model designed for advanced reasoning, coding, and long-horizon task execution. It uses a Mixture-of-Experts architecture with over one trillion parameters and a large active parameter set for efficient performance. The model supports an extended context window of up to one million tokens, allowing it to handle complex, multi-step workflows. It is built to perform autonomous tasks, including software development, system design, and engineering optimization. Benchmark results show strong performance across coding, reasoning, and agent-based evaluation tests. MiMo-V2.5-Pro incorporates hybrid attention mechanisms to improve efficiency while maintaining accuracy across long contexts. It is optimized for token efficiency, reducing the computational cost of running complex tasks. The model can integrate with development tools and frameworks to support real-world applications. It is designed to complete tasks that would typically require significant human effort over extended periods. Xiaomi has made the model open source, enabling developers to access and customize it. By combining performance, scalability, and efficiency, MiMo-V2.5-Pro pushes the boundaries of modern AI capabilities. -
16
MiMo-V2.5
Xiaomi Technology
Xiaomi MiMo-V2.5 is a next-generation open-source AI model that combines agentic intelligence with multimodal capabilities. It is designed to process and understand text, images, and audio within a single architecture. The model uses a sparse Mixture-of-Experts framework with a large parameter count to deliver efficient and scalable performance. It supports a context window of up to one million tokens, allowing it to handle long and complex workflows. MiMo-V2.5 integrates visual and audio encoders to improve perception and cross-modal reasoning. It is capable of performing tasks such as coding, reasoning, and multimodal analysis with strong accuracy. Benchmark results show competitive performance compared to leading AI models in both agentic and multimodal tasks. The model is optimized for token efficiency, balancing performance with lower computational cost. It is designed for real-world applications that require both reasoning and perception. Xiaomi has open-sourced the model, making it accessible for developers and researchers. By combining multimodality, scalability, and efficiency, MiMo-V2.5 pushes forward the development of advanced AI systems. -
17
UnoRouter
UnoRouter
Free tier, usage-basedUnoRouter serves as a versatile gateway for accessing various OpenAI-compatible language models. With a single API key, users can unleash over 200 models from multiple providers including OpenAI, Anthropic, Google, and others, seamlessly integrating coding agents like Claude Code, Cline, Codex, and Kilo Code. By simply directing any OpenAI SDK to the designated base URL, users can effortlessly switch between models without needing to modify their existing code. Additionally, UnoRouter features an integrated chat and character client, which supports personas, lorebooks, and the import of SillyTavern cards, all accessible with the same API key. The platform operates on a usage-based pricing model that includes a free tier, ensuring users have access to live updates on model availability and pricing. This innovative approach simplifies the process of utilizing multiple AI models for various applications. -
18
Ming-Flash Omni 2.0
Ant Group
Ming-Flash Omni 2.0, developed by Ant Group, represents a comprehensive large language model that operates on a cohesive multimodal framework, emphasizing a philosophy of “modal unity + task unity.” This model, as a part of the Ming series, is engineered to facilitate an integrated understanding and generation of content across various modalities, including text, images, audio, and video, thus eliminating the need for multiple specialized models to perform distinct tasks such as seeing, hearing, speaking, and drawing. Progressing from its predecessors, Ming-Light Omni and Ming-Flash Omni Preview, this iteration advances from validating a unified architecture and scaling to hundreds of billions of parameters to implementing a Data Scaling approach that achieves state-of-the-art performance in open-source environments across numerous benchmarks. Notably, the model encompasses four essential capability modules: image-text comprehension, video interpretation, speech generation, and image creation or manipulation. To enhance image-text understanding, Ming employs structured knowledge graphs that contribute to a more nuanced visual perception. This innovative approach not only broadens the model's applicability but also sets a new standard in the field of artificial intelligence. -
19
MiMo-V2-Omni
Xiaomi Technology
MiMo-V2-Omni is a powerful multimodal AI model engineered to process and understand multiple types of data, including text, code, and structured inputs, within a unified system. It is designed to power agent-based workflows, enabling the execution of complex, multi-step tasks with improved accuracy and efficiency. The model combines advanced reasoning capabilities with strong tool integration, allowing it to interact with external systems and automate workflows effectively. It supports a wide range of applications, from software development and data analysis to enterprise automation and research tasks. With enhanced contextual understanding, it can maintain coherence across long interactions and complex scenarios. MiMo-V2-Omni is optimized for real-world performance, ensuring reliability in practical use cases rather than just benchmark results. Its architecture enables efficient handling of large-scale tasks while maintaining speed and responsiveness. The model also supports seamless integration into existing platforms and workflows. By combining multimodal understanding with agentic execution, it provides a flexible and scalable solution for modern AI applications. Overall, it delivers a balance of intelligence, versatility, and efficiency for diverse use cases.