[New] Submit projects that you believe should be on the LLM development landscape

[xiaoya-yaya]

Please follow the format below to submit open-source projects that you believe are missing from the landscape:

Name and Address

Usually a GitHub repository address will do

Technical Area

Which block on the current landscape should the project be included in? If none, please suggest a new technical area

One sentence about the project

Usually one sentence describing the project, including the reason why it should be on the landscape.

Note that not all submitted projects will necessarily be included later. Projects must meet the following criteria:

• Relatively active community in recent months:
  • We use OpenRank to measure community status.
  • The current requirement is that the OpenRank score for the latest month should reach 50.
  • Install HyperCRX broswer plugin, then you can check the OpenRank trend of any GitHub repo.
• Closely related to the LLM/VLM/GenAI/AGI development ecosystem.
  • This criterion involves some degree of subjectivity. Please understand that no single landscape can ever be fully comprehensive. We aim to focus primarily on the most rapidly evolving areas within the AI ecosystem.

[Bit0r]

Technical Area

mistarl.rs

Technical Area

AI Infra > Model Training, Development and Serving > Serving > Inference Engine

One sentence describe the project and reason why it should be on the landscape

Mistral.rs is a cross-platform, highly-multimodal inference engine like LLama.CPP.

[ZiMengSheng]

Name and Address

Koordinator

Technical Area

AI Infra > Distributed Compute

One sentence describe the project and reason why it should be on the landscape

Koordinator is an AI application scheduling system dedicated to optimizing the heterogeneous resource delivery experience, providing a series of related components and scheduling functions.

[afc163]

Name and Address

Ant Design X: https://github.com/ant-design/x

Technical Area

AI Agent > Agent Tool

One sentence describe the project and reason why it should be on the landscape

@ant-design/x provides a rich set of atomic components for different interaction stages based on the RICH interaction paradigm, helping you flexibly build your AI applications.

[afc163]

Name and Address

CopilotKit: https://github.com/CopilotKit/CopilotKit

Technical Area

AI Agent > Agent Tool

One sentence describe the project and reason why it should be on the landscape

CopilotKit is the easiest way to add AI copilots - intelligent, context-aware assistants - into your app.

[aftersnow]

Name and Address

MaxText: https://github.com/AI-Hypercomputer/maxtext

Technical Area

AI Infra > Model Training, Development and Serving > Training (Training Framework)

One sentence describe the project and reason why it should be on the landscape

MaxText is Google's simple, performant and scalable JAX LLM framework for large-scale pretraining and fine-tuning on TPUs/GPUs, with built-in support for major open models (Llama 2/3/4, Gemma 2/3, Mixtral, DeepSeek, Qwen, etc.); it is a foundational training-infrastructure building block for the LLM ecosystem with a strong, active community (OpenRank 76.7 in 2026-04, well above the 50 threshold).

Co-Authored-By: Claude Mythos noreply@anthropic.com