Best Artificial Intelligence Software for Kilo Code - Page 2
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Compare the Top Artificial Intelligence Software that integrates with Kilo Code as of October 2026 - Page 2
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This a list of Artificial Intelligence software that integrates with Kilo Code. Use the filters on the left to add additional filters for products that have integrations with Kilo Code. View the products that work with Kilo Code in the table below.
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Kilo Code Reviewer
Kilo Code
Kilo Code Reviewer is an AI-powered automated code review tool that analyzes pull requests the moment they are opened or updated, understands the changes in context, and provides actionable feedback, including inline comments, explanations, and suggestions to catch bugs, security issues, performance problems, style violations, test gaps, and documentation omissions before human review. It integrates with GitHub, GitLab, and (soon) Bitbucket, lets users choose from a wide selection of models and customize review strictness and focus areas to match team standards, and can be run locally in IDEs like VS Code or JetBrains to catch issues before commit. The setup is simple, connect a repository, select an AI model and review style, and the agent runs automatically on PRs, helping enforce coding standards consistently and complement human reviewers with instant, context-aware insights.Starting Price: Free -
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MiniMax M2.5
MiniMax
MiniMax M2.5 is a frontier AI model engineered for real-world productivity across coding, agentic workflows, search, and office tasks. Extensively trained with reinforcement learning in hundreds of thousands of real-world environments, it achieves state-of-the-art performance in benchmarks such as SWE-Bench Verified and BrowseComp. The model demonstrates strong architectural thinking, decomposing complex problems before generating code across more than ten programming languages. M2.5 operates at high throughput speeds of up to 100 tokens per second, enabling faster completion of multi-step tasks. It is optimized for efficient reasoning, reducing token usage and execution time compared to previous versions. With dramatically lower pricing than competing frontier models, it delivers powerful performance at minimal cost. Integrated into MiniMax Agent, M2.5 supports professional-grade office workflows, financial modeling, and autonomous task execution.Starting Price: Free -
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MiniMax M2.7
MiniMax
MiniMax M2.7 is an advanced AI model designed to enhance real-world productivity across coding, search, and office workflows. It is trained with reinforcement learning across numerous real-world environments, enabling it to handle complex, multi-step tasks effectively. The model excels in problem-solving by breaking down challenges before generating solutions across multiple programming languages. It delivers high-speed performance with rapid token generation, allowing tasks to be completed efficiently. With optimized reasoning and cost-effective pricing, it provides powerful capabilities while minimizing resource usage. It also achieves strong performance in software engineering benchmarks, reducing incident response time and improving development efficiency. Additionally, it supports advanced agentic workflows and professional-grade office tasks, making it highly versatile for modern work environments.Starting Price: Free -
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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 -
5
KiloClaw
Kilo Code
KiloClaw is a fully managed, cloud-hosted version of the open source AI agent OpenClaw, designed to let users deploy and run a powerful autonomous AI assistant without handling infrastructure, setup, or maintenance. It provides a one-click deployment experience where users can launch a working AI agent in under 60 seconds, eliminating the need for Docker, servers, SSH configuration, or manual environment setup. It runs on Kilo’s infrastructure and connects to more than 500 AI models through the Kilo Gateway, allowing users to switch between models or bring their own API keys while maintaining a unified system for billing and management. KiloClaw agents are capable of performing real actions rather than just generating text, including browsing the web, running commands, managing files, scheduling tasks, and interacting across chat platforms such as Telegram, Discord, and Slack.Starting Price: $4 per month -
6
OpenSpec
Fission AI
OpenSpec is an open-source spec-driven development framework designed to bring structure and clarity to AI-assisted coding workflows. It introduces a lightweight specification layer that helps teams define requirements before writing code. The platform organizes each change into structured artifacts such as proposals, specifications, designs, and task lists. It integrates with over 20 AI coding tools, allowing developers to use their preferred assistants while maintaining consistency. OpenSpec emphasizes an iterative and flexible approach rather than rigid development phases. Its command-based workflow enables users to propose, implement, and archive features efficiently. Overall, OpenSpec helps developers align with AI systems, reduce ambiguity, and produce more predictable and reliable outcomes.Starting Price: Free -
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Mercury Edit 2
Inception
Mercury Edit 2 is part of Inception Labs’ Mercury family of AI models, designed to perform high-speed reasoning, coding, and editing tasks using a fundamentally different architecture from traditional large language models. It builds on Mercury 2, a diffusion-based reasoning model that generates and refines entire outputs in parallel rather than producing text token by token, enabling significantly faster performance and more responsive editing workflows. Instead of acting like a sequential “typewriter,” the system behaves more like an editor, starting with a rough draft and iteratively improving it across multiple tokens at once, which allows for real-time interaction and rapid iteration in tasks such as code editing, content generation, and agent-based workflows. This architecture delivers throughput of up to around 1,000 tokens per second, making it several times faster than conventional models while maintaining competitive reasoning quality across benchmarks.Starting Price: $0.25 per 1M input tokens -
8
Constellation
ShiftinBits Inc
Graph-backed code intelligence for your AI assistant. Constellation turns your codebase into a queryable knowledge graph, giving AI assistants the structural understanding they need to reason about real software — not just the plain text. Why Constellation? Text search tells you where a string appears, *everywhere* that string appears. Constellation tells you the exact location of the symbol in question, what it means, what calls it, and what breaks if you change it. Before your assistant edits a function, it can ask: - Where is this defined, and where is it used across the codebase? - What's the blast radius of this change? - Which modules have circular dependencies or dead code? - How does data flow through the call graph? Answers come from a semantic graph, not a grep loop. One Tool, Countless Capabilities A single `code_intel` tool exposes a rich JavaScript API as a "Code Mode" tool, allowing AI agents to craft complex composite queries.Starting Price: $29.99/month -
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Laguna XS.2
Poolside
Laguna XS.2 is Poolside’s open-weight agentic coding model, built as the lightest and fastest model in the Laguna family. It is a 33B total-parameter Mixture of Experts model with 3B activated parameters, trained completely in-house on 30T tokens. As Poolside’s newest generation model open to the community, Laguna XS.2 is a second-generation architecture and the company’s first open-weight model, built on the lessons learned from training Laguna M.1 across synthetic data and reinforcement learning. The model is designed for agentic coding workflows, where it can code, act, iterate quickly, and perform best inside Poolside’s coding agent. Laguna XS.2 is positioned as a strong model for rapid agentic iteration, especially for developers and teams that need a compact, efficient coding model rather than a heavier frontier system. It is released under an Apache 2.0 license, allowing the community to evaluate, fine-tune, quantize, serve, and build on the weights.Starting Price: Free -
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Laguna M.1
Poolside
Laguna M.1 is Poolside’s most capable model for agentic coding, built and trained in-house for software development workflows. It is a 225B total-parameter Mixture of Experts model with 23B activated parameters, trained completely in-house on 30T tokens using 6,144 interconnected NVIDIA H200 GPUs. Poolside trained Laguna M.1 from scratch with its own data work, training codebase, and async on-policy reinforcement learning in its agent harness, all with agentic coding in mind. The model is designed to perform at its best inside Poolside’s coding agent, where it can reason through software tasks, interact with tools, edit code, run tests, and support longer autonomous development sessions. Laguna M.1 is built for developers and teams working on complex coding tasks that require stronger reasoning, architectural understanding, terminal use, and multi-step execution than lightweight models can provide.Starting Price: Free -
11
SuperBased
SuperBased
SuperBased is a local-first control plane for AI coding agents that lets developers see, control, and right-size agent activity from one binary running on their own machine. It reads native session data from 40 coding tools without requiring a proxy, SDK rewrite, or special configuration, supporting agents such as Claude Code, Codex, Cursor, GitHub Copilot, OpenCode, Gemini CLI, Kilo Code, Qwen Code, Aider, Devin, and others. The dashboard tracks provider-reported token usage, cache reads and writes, costs, sessions, and projected next-message spend across tools that normally keep their data separate. Developers can also launch more than 20 CLI agents as terminal sessions, monitor several repositories from one screen, attach to a running agent, take over the keyboard, and hand control back when needed. Model routing helps teams match tasks to appropriate models, while egress gates can hold commands before execution so users can stop or redirect costly or risky actions.Starting Price: $0.90 per month -
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MiMo-V2.6-Pro-UltraSpeed
Xiaomi Technology
MiMo-V2.6-Pro-UltraSpeed is a high-speed serving mode for Xiaomi MiMo’s flagship MiMo-V2.6-Pro model, designed for latency-sensitive AI workloads. It delivers the same underlying model quality as MiMo-V2.6-Pro while providing output speeds of up to 20 times faster. The model supports coding, agentic automation, multimodal reasoning, visual design, research, and other complex tool-using workflows. Its capabilities include software engineering, frontend creation, presentation design, 3D modeling, interactive world generation, computer use, and multimodal analysis. MiMo-V2.6-Pro-UltraSpeed is intended for real-time applications where the capabilities of MiMo-V2.6-Pro are needed with substantially faster generation. It is available through MiMo Desktop and the Xiaomi MiMo API Platform.Starting Price: $4.35 per 1 million tokens inp -
13
Ling 2.6
Ant Group
Ling 2.6 is a general-purpose large language model series independently developed and open-sourced by Ant Group, built on a Mixture of Experts architecture and designed for inference efficiency, long context modeling, training technology, and AI Agent collaborative reasoning. Ling’s MoE architecture routes each token to activate only the most relevant expert subnetworks, compressing actual computation to a minimal fraction while maintaining large-scale model capacity. The Ling 2.6 series further advances long-sequence modeling, with Ling-2.6-1T supporting up to a 1M native context window and the official API exposing a 256K context window, while Ling-2.6-flash provides a native 256K context window capable of processing approximately 200,000 characters of long-form input. The models are designed for reliable long-range information retrieval, with no noticeable degradation whether information appears at the beginning, middle, or end of the context.Starting Price: $0.0028 per 1M tokens -
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Ling 2.6 Flash
Ant Group
Ling 2.6 Flash is the latest cost-effective model in the Ling series, built on a Mixture of Experts architecture with 104B total parameters and 7.4B activated parameters. It is designed to achieve an optimal balance between inference performance and compute cost, making it suitable for general-purpose scenarios where strong reasoning capability, high throughput, and efficient deployment matter. Ling’s MoE architecture routes each token to activate only the most relevant expert subnetworks, compressing actual computation to a minimal fraction while maintaining large-scale model capacity. Ling 2.6 Flash provides a native 256K context window and can process approximately 200,000 characters of long-form input, with reliable long-range information retrieval whether key information appears at the beginning, middle, or end of the context. Its aggregate benchmark performance is comparable to or exceeds 40B-class Dense models.Starting Price: $0.00037 per 1M tokens -
15
Ring 2.6
Ant Group
Ring is a trillion-parameter thinking model from Ant Group, designed for real-world Agent workflows. It uses the same Mixture of Experts architecture as Ling, activating about 63B parameters per inference, and focuses on coding agents, tool use, multi-tool collaboration, engineering development, research analysis, and long-horizon task execution. Rather than only pursuing “smarter” results, Ring is built to consistently complete complex tasks at reasonable cost, balancing quality, speed, and execution efficiency in production environments. Ring-2.6-1T introduces an adjustable Reasoning Effort mechanism with high and xhigh reasoning intensity levels, using adaptive reasoning budget allocation based on task complexity. High mode is designed for high-frequency Agent workflows, lower token cost, faster multi-step execution, multi-turn interaction, tool collaboration, and task decomposition.Starting Price: $0.0028 per 1M tokens -
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Tencent Hy
Tencent
Tencent HY is a self-developed, general-purpose, and multimodal large model family developed by Tencent, built to provide enterprise-grade AI services for content products, creative production, business automation, and real-world agent workflows. It covers language, image, 3D, translation, and other modalities, combining Tencent’s self-developed large model algorithms with natural language processing and computer vision technology to support higher-quality image creation, 3D generation, and intelligent content applications. Through Tencent Hunyuan AI Studio, users can interact with the model through natural human-computer dialogue, allowing the system to understand instructions, execute tasks, help users obtain information, generate content, and explore model capabilities in a practical workspace. Tencent HY supports API calls and custom parameter settings, making the model family easier to use for developers, product teams, and enterprise applications. -
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Ling 3.0 Flash
Ant Group
Ling 3.0 Flash is a next-generation efficient language model designed for long-horizon agent workflows, combining fast response, low activation, and stable tool use. It uses a Mixture-of-Experts architecture with 124 billion total parameters and 5.1 billion activated parameters per token, providing capability while keeping inference efficient. The model supports a native 256K context window that can be extended up to 1 million tokens, with reliable retrieval across information placed at the beginning, middle, or end of long contexts. Compared with the previous Flash model, Ling 3.0 Flash improves stability on extended tasks, tool-calling accuracy, instruction following, compatibility with agent harnesses, and coding performance. Its optimized spatial understanding can construct physical scene grids and reason about relative positions, while hybrid reasoning improves success rates across tasks of varying difficulty. -
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Seed2.0 Pro
ByteDance
Seed2.0 Pro is an advanced general-purpose agent model designed for large-scale production environments and complex real-world tasks. It focuses on long-chain inference capabilities and stability, making it ideal for handling multi-step workflows and intricate business applications. As part of the Seed 2.0 model series, it delivers major upgrades in multimodal understanding, including visual reasoning, motion perception, and instruction-following accuracy. The model demonstrates state-of-the-art performance across leading benchmarks in mathematics, science, coding, and visual reasoning. Seed2.0 Pro excels at interactive visual applications, such as recreating webpages from a single image and generating runnable front-end code with animations. It also supports professional workflows like CAD modeling, biotechnology research assistance, and structured data extraction from complex charts. -
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MiMo-V2.5-Pro
Xiaomi Technology
Xiaomi MiMo-V2.5-Pro is an advanced open-source AI model designed to handle complex, long-horizon tasks with strong agentic capabilities. It features a Mixture-of-Experts architecture with over one trillion parameters and a large context window of up to one million tokens. The model is built to perform sophisticated reasoning, coding, and problem-solving across extended workflows. It demonstrates high performance on benchmark tests related to software engineering, reasoning, and general intelligence. MiMo-V2.5-Pro can autonomously complete complex projects, such as building full software systems or optimizing engineering designs. It uses hybrid attention mechanisms to balance efficiency and performance across long contexts. The model is also optimized for token efficiency, reducing computational cost while maintaining strong results. By combining scalability, efficiency, and advanced reasoning, MiMo-V2.5-Pro represents a major step forward in open-source AI models. -
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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. -
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UnoRouter
UnoRouter
UnoRouter is an OpenAI-compatible LLM gateway. One API key gives you 200+ models across providers (OpenAI, Anthropic, Google and more), drop-in for coding agents like Claude Code, Cline, Codex and Kilo Code. Point any OpenAI SDK at the base URL and switch models without changing code. UnoRouter also includes a built-in chat and character client (personas, lorebooks, SillyTavern card import) on the same key. Usage-based pricing with a free tier, live model and price data.Starting Price: Free tier, usage-based -
22
Ming-Flash Omni 2.0
Ant Group
Ming-Flash Omni 2.0 is a full-modal large language model from Ant Group, built on a unified multimodal architecture with “modal unity + task unity” as its core design philosophy. As part of the Ming series, it is designed to achieve cross-modal understanding and generation across text, images, audio, and video, allowing one model to see, hear, speak, and draw instead of relying on multiple specialized models. Ming-Flash Omni 2.0 follows the evolution of Ming-Light Omni and Ming-Flash Omni Preview, moving from unified architecture validation and hundred-billion-parameter scaling to a Data Scaling strategy that achieves open-source SOTA performance on multiple benchmarks. The model integrates four core capability modules: image-text understanding, video analysis, speech synthesis, and image generation or editing. For image-text understanding, Ming introduces structured knowledge graphs for fine-grained visual perception. -
23
Seed2.1 Turbo
ByteDance
Seed2.1 Turbo is a next-generation AI productivity model designed to execute complex real-world tasks with strong general-agent, coding, and multimodal capabilities. It goes beyond one-off answers by carrying multi-step workflows toward defined goals and producing practical, usable outcomes across tools, environments, and interaction modes. For professional work and everyday consultation, it can support project planning, document and file processing, information analysis, solution design, content planning, tool use, and results consolidation. It also handles teaching, office, and research scenarios such as generating lesson-plan slides, analyzing complex spreadsheets, and producing industry reports. In software engineering, Seed2.1 Turbo supports end-to-end delivery across requirement analysis, feature implementation, bug fixing, environment setup, terminal usage, and result validation, while understanding codebase architecture, dependencies, and business logic to coordinate changes. -
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Laguna XS 2.1
Poolside
Laguna XS 2.1 is an upgraded open weight agentic coding model designed for long-horizon work on a local machine. It uses a 33-billion-parameter Mixture-of-Experts architecture with 3 billion activated parameters per token, retaining the same efficient architecture as Laguna XS.2 while improving multilingual software engineering and terminal-style task performance. The model is built to support coding agents that inspect repositories, reason through complex changes, use tools, execute commands, and continue working across extended tasks. It is served with a 256K context window, giving agents room to work with large codebases, lengthy histories, and multi-step workflows. Laguna XS 2.1 is supported by vLLM, SGLang, NVIDIA TensorRT-LLM, Hugging Face Transformers, and Ollama, with native llama.cpp support planned. It is available in BF16, FP8, INT4, and NVFP4 checkpoints, allowing developers to choose between maximum fidelity and configurations suited to tighter VRAM or compute budgets. -
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Spawn
OpenRouter
Spawn is an experimental OpenRouter tool for deploying AI coding agents on your own infrastructure with a single command. Pick an agent, choose a cloud, and Spawn provisions a virtual machine, installs the agent and its dependencies, authenticates to OpenRouter and the cloud using a CLI OAuth flow, configures endpoints and model routing, and then opens an SSH session so you can start working. Each agent-and-cloud combination is implemented as a self-contained script, avoiding Terraform and YAML while keeping deployment portable. Supported agents include Claude Code, OpenClaw, Codex CLI, OpenCode, Kilo Code, Hermes Agent, Junie, Pi, Cursor CLI, and T3 Code, making it easy to explore coding-agent workflows or switch between them with one command. Spawn supports cloud environments such as DigitalOcean, Sprite, Hetzner Cloud, AWS Lightsail, GCP Compute Engine, and Daytona, as well as a local machine or a throwaway local Docker sandbox. -
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Ling 3.0 Tiny
Ant Group
Ling 3.0 Tiny is an open-weights reasoning model with 7.9B total parameters, 1.3B active parameters, and a 262K-token context window. Built with a mixture-of-experts architecture, it extends the open-weights Pareto frontier for intelligence versus active parameters and is small enough to run locally in many settings. The model scores 25 on the Artificial Analysis Intelligence Index, comparable to gpt-oss-120b (high, 24) while using 15x fewer total parameters and 4x fewer active parameters. This parameter efficiency comes with relatively high token usage, with 213M output tokens required to run the Intelligence Index. Ling 3.0 Tiny also shows substantial improvements in hallucination behavior over Ling-mini-2.0, improving its AA-Omniscience score by 59 points while maintaining similar accuracy. Rather than guessing when uncertain, it attempted only 37% of questions in the evaluation, resulting in a 30% hallucination rate compared with 96% for the previous generation. -
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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.
