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Description

Deploy the open-source buildkite-agent within your own environment for optimal speed, enhanced control, and robust security. This agent is responsible for checking out your source code, executing tailored hooks and overrides, and subsequently carrying out your build tasks, ensuring that your source code remains securely on your own infrastructure. You can easily install the agent via a variety of packages and binaries compatible with numerous platforms and architectures, such as Ubuntu, Debian, Mac, Windows, Docker, and many others. With its artifact and metadata storage capabilities, the agent facilitates share-nothing, state-free build jobs that can be effortlessly distributed and scaled across multiple agents. You have the flexibility to run as many build agents as you require (up to 10,000 connected per account), all while maintaining smooth operations. The open-source Elastic CI Stack for AWS provides a straightforward method to maintain a scalable CI stack that adapts to your needs within your own AWS account. Alternatively, if you prefer a more personalized approach, you have the option to leverage the tools with which you are already familiar in your production environments, such as Packer and Terraform, allowing for a seamless integration of your existing workflows. This adaptability ensures that your CI/CD processes can evolve alongside your project requirements.

Description

MiMo-V2.6-Pro is an open-source, natively omnimodal AI model from Xiaomi MiMo designed for coding, agentic workflows, visual creation, research, and computer-based tasks. It is the highest-capability model in the MiMo-V2.6 series and was trained using a large-scale reinforcement learning process focused on verifiable, complex tasks. The model can handle software engineering, automation, tool use, visual reasoning, and long-running agent workflows across multiple environments. Its multimodal capabilities extend beyond traditional coding into 3D scene generation, Blender modeling, embodied simulation, frontend development, presentation design, video creation, and music composition. MiMo-V2.6-Pro can take text, images, video, and other visual inputs and coordinate multi-agent workflows to produce and iteratively refine complex outputs. Research applications demonstrated by Xiaomi include materials discovery, literature analysis, computational simulation, hypothesis generation, and formalizing mathematical proofs in Lean. Xiaomi has released the model alongside its technical report, reinforcement learning environments, and RL code so researchers can study and reproduce the training approach. MiMo-V2.6-Pro is also available in an UltraSpeed configuration that provides substantially faster output for latency-sensitive workflows. Users can access the model through MiMo Desktop, AI Studio, MiMo Code, the MiMo API Platform, OpenRouter, and Hugging Face.