Changelog

<img src="https://apertis.ai/images/kilo-partner-announcement.png" alt="AWS Partner Announcement" width="450">

Apertis is now available as an official built-in model provider in Kilo CLI and Kilo Code. Users can select Apertis directly from the provider list without any manual endpoint configuration.

What's new:

• Apertis appears as a built-in provider option in Kilo CLI and Kilo Code
• Select from 500+ AI models across 30+ providers directly in the provider menu
• No manual API base URL setup required — just choose Apertis, enter your API key, and go

How to use:

1. Open Kilo CLI or Kilo Code 2. Go to provider settings 3. Select Apertis from the provider list 4. Enter your Apertis API key 5. Choose your preferred model and start coding

We now support an apertis/ namespace prefix for all model IDs, designed specifically for Cursor IDE users who experience model ID collisions with Cursor's built-in model routing.

How It Works

When your model ID overlaps with Cursor's built-in models, simply add the apertis/ prefix to ensure requests route through Apertis:

The apertis/ prefix is automatically stripped on our end — all downstream processing (model validation, channel routing, billing, and logging) uses the original model ID. Fully compatible with existing suffixes like :web and code: prefix and all models.

Model Detail Page

Each model's detail page now includes a Cursor IDE Model IDs section listing all available apertis/-prefixed identifiers. Click to copy, and hover the infoicon for context.

Happy Building

Our AI infrastructure is powered by Amazon Bedrock, providing enterprise-grade reliability and compliance for all users.

• AWS Partner Network: Registered as Apertis AI (Stima AI LLC), Partner status Active
• Powered by Amazon Bedrock: Direct access to Claude models (Sonnet, Opus, Haiku) via AWS infrastructure
• Footer trust badges: Added AWS Partner Network Member and Powered by Amazon Bedrock badges alongside existing OWASP, NIST CSF, and PCI DSS compliance indicators

Happy Building.

MiMo-V2-Pro

MiMo-V2-Pro is Xiaomi's flagship foundation model with over 1T parameters and a 1M-token context window, optimized for advanced agentic workflows. It is highly adaptable to general agent frameworks such as OpenClaw, delivering strong performance in complex, real-world task execution. Ranking among the top tier on benchmarks like PinchBench and ClawBench, with performance approaching models like Opus 4.6, MiMo-V2-Pro is designed to act as the core intelligence of agent systems, orchestrating workflows, driving production engineering tasks, and delivering reliable results at scale.

MiMo-V2-Omni

MiMo-V2-Omni is a frontier omni-modal model that natively processes image, video, and audio inputs within a unified architecture. It combines strong multimodal perception with advanced agentic capabilities, including visual grounding, multi-step planning, tool use, and code execution. With a 256K context window, MiMo-V2-Omni is well suited for complex real-world tasks that span multiple modalities, enabling integrated reasoning and execution across diverse input types.

Happy Building.

MiniMax M2.7

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. It incorporates advanced multi-agent collaboration, enabling the model to plan, execute, and iteratively refine complex tasks across dynamic environments.

Built for production-grade workflows, M2.7 supports tasks such as live debugging, root cause analysis, financial modeling, and full document generation across Word, Excel, and PowerPoint. With strong benchmark performance—including 56.2% on SWE-Pro, 57.0% on Terminal Bench 2, and 1495 ELO on GDPval-AA—it sets a new standard for multi-agent systems in real-world digital workflows.

Happy Building