Find and compare the best Artificial Intelligence software for YAML in 2026
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Use the comparison tool below to compare the top Artificial Intelligence software for YAML on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Preloop
Preloop
$290 per monthPreloop serves as an open-source control plane designed for AI agents that perform tangible actions. It integrates a multi-layered security approach featuring an MCP firewall for managing tool access, an AI model gateway that ensures cost-effectiveness, safety, and accountability, along with policy-as-code that incorporates human oversight, all while providing runtime session visibility and audit trails—all within a self-hosted environment. Given the rapid capabilities of AI agents to deploy code, modify infrastructure, manage financial transactions, access production data, and incur model costs almost instantaneously, Preloop empowers teams to regulate agent activities, monitor expenditures, and determine which actions necessitate human consent. It is compatible with a variety of tools such as OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any agents that adhere to MCP standards. Additionally, access rules can evaluate not only the tool names but also arguments and context, utilizing CEL expressions to establish detailed conditions. Furthermore, teams have the flexibility to initiate with observability features and progressively introduce approval and denial protocols without the need for SDKs or extensive modifications to existing applications, thus streamlining the implementation process. This comprehensive approach ensures that organizations remain in control of their AI agents' functionalities and impacts. -
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Ornith-1.0
DeepReinforce
FreeOrnith-1.0 represents an innovative family of models tailored specifically for coding tasks that require agentic capabilities. This family encompasses a wide range of models, from the compact 9B Dense versions ideal for deployment on edge devices to the expansive 397B MoE frontier-scale models designed for peak performance, including variants such as 9B Dense, 31B Dense, 35B MoE, and 397B MoE. Built upon the foundational strengths of pretrained models like Gemma 4 and Qwen 3.5, Ornith-1.0 excels in achieving top-tier performance among open-source models that are similar in size when evaluated against coding benchmarks. A significant breakthrough of this model is its self-improving training framework, which effectively learns to produce both solution rollouts and the tailored scaffolds that direct those rollouts. Rather than depending on static, human-crafted harnesses, Ornith-1.0 perceives the scaffold as a dynamic entity that evolves alongside the policy, enabling the model to optimize both the orchestration of tasks and the resulting solutions in tandem. This dual optimization approach enhances the model's adaptability and effectiveness in real-world coding scenarios. -
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Gemini 3.5 Flash-Lite
Google
$0.30 per 1M input tokensGemini 3.5 Flash-Lite stands out as the quickest model within Google's Gemini 3.5 lineup, specifically engineered for tasks requiring low latency and for enhancing developer workflows that demand high throughput, including agentic search, document processing, coding, and extensive data analysis. It boasts an impressive output capacity of 350 tokens per second and marks a significant enhancement over earlier Flash-Lite iterations in terms of both quality and agentic capabilities. Developers have the flexibility to adjust the model's thinking level to suit the demands of the task at hand: minimal or low thinking allows for rapid processing of large volumes, while elevated thinking levels accommodate more intricate, multi-step workflows involving subagents. Furthermore, the model is equipped with built-in computational skills, enabling it to interact effectively with various digital environments across compatible platforms. Additionally, Gemini 3.5 Flash-Lite excels in coding, comprehending long contexts, and executing real-world tasks, consistently outperforming its predecessor, Gemini 3.1 Flash-Lite, in critical assessments and even exceeding the performance of Gemini 3 Flash on multiple benchmarks related to agentic functions and software engineering. This impressive performance highlights its potential to transform how developers approach complex workflows and data-intensive tasks. -
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Kastra
Kastra
$19.99 per monthKastra serves as the crucial authorization framework for AI systems, determining the permissions of agents, models, and tools prior to their execution. Positioned along the execution path of all interactions such as prompts, tool calls, shell commands, database operations, and API requests, it evaluates each action based on deterministic, attribute-driven policies, rendering decisions to allow, deny, redact, or escalate in less than a millisecond. In contrast to monitoring solutions that only track AI actions post-execution, Kastra proactively prevents unauthorized activities before they can impact any tool, API, database, or production environment. Its comprehensive control plane integrates a policy engine, edge decision-making capabilities, various integrations, and a tamper-proof evidence vault that securely signs each decision for auditing and replay purposes. Furthermore, with Kastra Edge, local enforcement is extended to developer environments, safeguarding coding agents such as Claude Code, Cursor, and Codex CLI from harmful commands, unauthorized data extraction, unsafe file modifications, and improper tool usage. This proactive approach to authorization not only enhances security but also ensures compliance and accountability in AI-driven processes. -
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Better Claw
Better Claw
$49 per monthBetterClaw serves as a no-code platform for teams seeking effective AI agents without the need for complex infrastructure. Users can simply describe tasks through a chat interface, link various tools and LLM providers, and deploy autonomous agents without the hassles of Docker, YAML, configuration files, or VPS hosting. These agents can operate on set schedules across platforms like Telegram, Slack, Discord, Gmail, and custom webhooks, while the system provides visibility into task states, categorizing them as backlog, ready, running, successful, or failed, with the ability to re-queue unsuccessful attempts. The platform supports any skill compatible with OpenClaw and features a selection of curated skills that have undergone a rigorous four-layer security audit. Teams can transform successful interactions into reusable skills, integrate with over 30 LLM providers, and have agents generate tangible outputs such as PDFs, DOCX files, XLSX/CSV spreadsheets, images, audio, video, and Markdown, eliminating the need for manual text copying. Enhanced security measures are in place, including AES-256 encryption for credentials, dedicated containers for each agent, automatic secret purging every five minutes, specific credential grants per agent, and comprehensive access audit logs to ensure safe operations. Overall, BetterClaw empowers teams to streamline their workflows while maintaining a high level of security and efficiency. -
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Holo4
H Company
$0.40 per 1M tokens (input)Holo4 is H Company's series of generalist computer-use and agentic AI models built to perform multi-step work across software interfaces. It is available as Holo4 27B, a dense 27-billion-parameter model, and Holo4 35B-A3B, a Mixture-of-Experts model containing 35 billion total parameters with 3 billion active. Holo4 can interact with applications by clicking and typing through graphical interfaces, writing and executing code, or calling MCP and API tools. The same model can operate across desktops, websites, Android devices, code sandboxes, and business APIs without requiring developers to select a separate specialized model for each environment. H Company trained Holo4 using 127 billion supervised fine-tuning tokens, with approximately three-quarters consisting of successful agentic trajectories spanning desktop, web, MCP/API, and mobile tasks. Reinforcement learning then trained separate experts for desktop and web interaction and for terminal, MCP, and API work before merging them into a single model. Holo4 27B scored 85.2% on OSWorld, 61.7% on OSWorld 2.0, 45.4% on AutomationBench, and 85.1% on AndroidWorld in the evaluations reported by H Company. The models support a 256K context window, with the 27B model positioned for greater accuracy on long multi-step tasks and the 35B-A3B version positioned as a faster and less expensive alternative. Holo4 is available through a hosted API and downloadable model weights, enabling developers and enterprises to build agents that perform workflows spanning multiple applications and interaction methods. -
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PowerShell
Microsoft
FreePowerShell serves as a versatile task automation and configuration management framework that operates across various platforms and is comprised of both a command-line shell and a scripting language. Distinct from typical shells that primarily handle text, PowerShell is founded on the .NET Common Language Runtime (CLR), allowing it to work with .NET objects instead. This core distinction introduces a range of innovative tools and techniques for automating tasks. Unlike conventional command-line interfaces, PowerShell cmdlets are specifically crafted to manipulate objects rather than mere text. An object represents organized information that transcends the simple string of characters displayed on your screen. The output generated by commands always includes additional metadata that can be leveraged when necessary. If you've utilized text-processing tools previously, you'll notice that their functionality differs when employed within PowerShell. Generally, there is no need for separate text-processing utilities to obtain specific information, as you can directly interact with segments of the data using the standard PowerShell object syntax. This capability enhances the user experience by allowing for more intuitive and powerful data manipulation. -
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JetBrains Fleet
JetBrains
Developed entirely from the ground up, JetBrains Fleet draws on two decades of experience in creating integrated development environments (IDEs). It utilizes the robust IntelliJ code-processing engine, featuring a distributed architecture and a fresh user interface designed for modern developers. Our aim with Fleet was to create a swift and efficient text editor that allows for quick code browsing and editing. It launches almost instantaneously, enabling you to start your work without delay, and has the capability to seamlessly evolve into a full-fledged IDE, with the IntelliJ engine operating independently from the editing interface. Fleet encompasses all the beloved features of IntelliJ-based IDEs, such as code completion tailored to your project context, easy navigation to definitions and usages, real-time code quality assessments, and convenient quick-fixes. The architecture of Fleet is thoughtfully designed to accommodate various configurations and workflows, allowing it to run locally on your machine or to offload some processes to the cloud, showcasing its versatility and adaptability for different development needs. This flexibility ensures that developers can choose the setup that best fits their workflow requirements. -
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DevBox
DevBox
$25 one-time paymentDevBox offers an extensive collection of 71 handcrafted tools, including generators, converters, encoders, and more, along with 20 cheat sheets and 65 code snippets tailored for both developers and designers, all accessible across various platforms. Operating entirely offline ensures that your sensitive data remains secure, as it is not transmitted outside the application. Each tool delivers immediate feedback based on your interactions, allowing you to view results in real-time without any delays. Furthermore, a variety of viewers are available to help you quickly access data in different formats such as CSV, JSON, and JWT. The formatters and converters function dynamically as you type, making downloading or copying content just a click away. Additionally, DevBox includes 20 cheat sheets covering codes, services, and numerous CLI tools, making it an invaluable resource for efficient development and design. With its comprehensive set of features, DevBox stands out as a powerful tool for enhancing productivity for users in the tech space. -
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Empower hybrid cloud developers across all skill levels to create code with the help of AI-driven suggestions. Imagine having the ability to convert simple English phrases into functional code; IBM watsonx Code Assistant makes that a reality. Leveraging the capabilities of IBM watsonx.ai foundation models (FM), this tool simplifies the coding process by offering AI-generated recommendations, thus extending IT automation benefits throughout your organization and making it a valuable resource for a broader audience beyond just technical experts. This innovative approach allows for real-time code suggestions tailored to developers' natural language queries. Furthermore, IBM watsonx Code Assistant is built with watsonx.ai FMs that are specifically designed for efficiency in deployment, allowing organizations to tailor the models to their needs while adhering to enterprise standards and best practices. As a result, this tool not only enhances productivity but also democratizes coding, allowing more individuals to contribute to software development initiatives.
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doteval
doteval
doteval serves as an AI-driven evaluation workspace that streamlines the development of effective evaluations, aligns LLM judges, and establishes reinforcement learning rewards, all integrated into one platform. This tool provides an experience similar to Cursor, allowing users to edit evaluations-as-code using a YAML schema, which makes it possible to version evaluations through various checkpoints, substitute manual tasks with AI-generated differences, and assess evaluation runs in tight execution loops to ensure alignment with proprietary datasets. Additionally, doteval enables the creation of detailed rubrics and aligned graders, promoting quick iterations and the generation of high-quality evaluation datasets. Users can make informed decisions regarding model updates or prompt enhancements, as well as export specifications for reinforcement learning training purposes. By drastically speeding up the evaluation and reward creation process by a factor of 10 to 100, doteval proves to be an essential resource for advanced AI teams working on intricate model tasks. In summary, doteval not only enhances efficiency but also empowers teams to achieve superior evaluation outcomes with ease. -
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Spawn
OpenRouter
Spawn serves as an innovative tool within OpenRouter for effortlessly deploying AI coding agents on your infrastructure using just a single command. You can select your desired agent, pick a cloud provider, and Spawn will take care of provisioning a virtual machine, installing the chosen agent along with its necessary dependencies, authenticating to both OpenRouter and the cloud via a CLI OAuth process, configuring all required endpoints and model routing, and finally initiating an SSH session so you can begin your tasks immediately. Each combination of agent and cloud is encapsulated in a standalone script, thus eliminating the need for Terraform or YAML and ensuring that deployments remain portable. The agents supported include Claude Code, OpenClaw, Codex CLI, OpenCode, Kilo Code, Hermes Agent, Junie, Pi, Cursor CLI, and T3 Code, which simplifies the exploration of various coding-agent workflows or allows for seamless switching between them with a single command. In addition to cloud platforms such as DigitalOcean, Sprite, Hetzner Cloud, AWS Lightsail, GCP Compute Engine, and Daytona, Spawn also accommodates local setups or ephemeral local Docker environments. This versatility ensures that developers can choose the best environment suited to their needs. -
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GPT-5.6 Sol Ultrafast
OpenAI
The new OpenAI API service tier, GPT-5.6 Sol Ultrafast, operates up to 14 times quicker than the Standard processing version, delivering cutting-edge intelligence to applications and workflows where every fleeting moment is crucial. Utilizing Cerebras technology, it boasts the capability to produce as many as 750 output tokens each second, enabling sophisticated reasoning to function at real-time velocities without the need for a more compact or specialized model. This service is particularly tailored for business environments where rapid responses can significantly enhance the capabilities of AI systems. It has various applications, including incident response, where it can swiftly analyze logs, code changes, traces, and engineering reports during ongoing outages; financial research and security, where it can rapidly evaluate fluctuating market signals and identify suspicious transactions; and customer support, where intricate problems can be resolved seamlessly during live conversations. In the realm of e-commerce, it excels at handling product inquiries, verifying inventory status, and customizing product recommendations to enhance user experience. By implementing this advanced service, organizations can expect improved efficiency and effectiveness in their operations. -
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Gemini 3.8 Flash Cyber
Google
Gemini 3.8 Flash Cyber represents Google's most advanced cybersecurity model, offering top-tier performance in identifying vulnerabilities and automating patching processes with remarkable speed for rapid iteration. Tailored for trusted defenders, it is accessible via the Fairwind Program. On CyberGym, a recognized industry benchmark for detecting vulnerabilities, this model showcases exceptional autonomous vulnerability discovery, outperforming both Gemini 3.5 Flash Cyber and larger frontier models. Furthermore, Google assessed its effectiveness on an internal benchmark that spans complex codebases across 20 programming languages, achieving a success rate of over 70% in identifying various vulnerabilities. Unlike many models that focus on offensive strategies, Gemini 3.8 Flash Cyber emphasizes the importance of fixing vulnerabilities, providing defenders with advanced tools that enhance their ability to stay ahead of cyber attackers. This focus on proactive defense represents a crucial shift in the cybersecurity landscape, prioritizing the safeguarding of systems over mere exploitation capabilities. -
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Grok 4.8
SpaceXAI
Grok 4.8 is an upcoming large language model from xAI designed to continue the company’s push toward more capable coding, reasoning, knowledge work, and autonomous AI agents. Elon Musk has stated that Grok 4.8 uses approximately 2.5 trillion parameters, making it larger than the 2.1-trillion-parameter Grok 4.7 model previously discussed. The model is also being trained on a new C++ software stack that xAI expects to use for its next generation of large-scale training runs. Initial model training is expected to finish before reinforcement learning and additional post-training work begin, meaning the final production model is not yet available. Based on the current Grok generation, Grok 4.8 is likely to emphasize software engineering, agentic tool use, professional knowledge work, image understanding, and complex multi-step reasoning. Grok 4.7 currently supports configurable reasoning levels and a 500,000-token context window, providing a baseline for the capabilities xAI is developing further. Grok 4.8 may also become an important model for products such as Grok Build and Grok Bot, where stronger reasoning and tool coordination can support longer autonomous workflows. xAI has not published official Grok 4.8 benchmarks, pricing, context limits, API details, or an exact release date. Grok 4.8 is expected to serve developers, engineering teams, researchers, enterprises, and AI agent builders seeking frontier-level performance across technical and professional tasks. -
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Claude Fable 5.5
Anthropic
Claude Fable 5.5 is an anticipated but currently unannounced model in Anthropic's Claude family, and Anthropic has not confirmed that a model with this name will be released. As of September 30, 2026, Claude Fable 5.1 remains the latest officially documented Fable model. Fable represents Anthropic's highest-end model tier for demanding reasoning and long-horizon agentic work, while the newer Opus 5.5 and Sonnet 5.5 occupy lower-cost positions in the Claude lineup. Anthropic's current documentation gives Fable 5.1 a 1-million-token context window and maximum output length of 128,000 tokens. It supports text and image inputs with text output and uses adaptive thinking that remains active throughout model operation. Fable 5.1 defaults to high reasoning effort and is listed as having a June 2026 reliable knowledge cutoff and training-data cutoff. API pricing is $10 per million input tokens and $50 per million output tokens, while prompt-cache reads cost $0.25 per million tokens and Batch API processing receives a 50% input and output discount. Anthropic's official documentation currently provides model identifiers for Fable 5.1 across the Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry, and Claude Platform on AWS. No equivalent model identifier, specifications, benchmark results, pricing, availability information, or release schedule has been published for Claude Fable 5.5.
