RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.
mamba-architecture
mamba-architecture is an open-source productivity skill for Claude Code and compatible agents, published by Orchestra-Research. Its author describes it as: “State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-…”. The project has 12k stars on GitHub and is available under the MIT license. Add it to your setup with `/plugin marketplace add Orchestra-Research/AI-Research-SKILLs`.
What mamba-architecture does
Mamba is a state-space model architecture achieving O(n) linear complexity for sequence modeling.
Installation
Add mamba-architecture to your agent with:
/plugin marketplace add Orchestra-Research/AI-Research-SKILLsAlways review a skill's source before installing it. This command comes from the skill's public repository; the linked repo is the source of truth for exact setup steps.
What's inside
The SKILL.md for mamba-architecture is organised into these sections:
- Quick start
- Common workflows
- Workflow 1: Language model with Mamba-2
- Workflow 2: Use pretrained Mamba models
- Workflow 3: Mamba-1 vs Mamba-2
- Workflow 4: Benchmark vs Transformers
- When to use vs alternatives
- Common issues
- Advanced topics
- Hardware requirements
- Resources
When to use it
Reach for mamba-architecture when you want productivity help from your agent without writing the same instructions every session. Load the skill and the agent picks it up automatically for relevant tasks.
Strengths
- Clear MIT license — safe to read and adapt
- Ships in Orchestra-Research/AI-Research-SKILLs, an established project with 11,807 GitHub stars
- Actively maintained (recent commits)
Topics
Frequently asked questions
- What does mamba-architecture do?
- State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.
- How do I install mamba-architecture?
- Run /plugin marketplace add Orchestra-Research/AI-Research-SKILLs in your agent, then reload your skills. Review the source at https://github.com/Orchestra-Research/AI-Research-SKILLs before installing.
- Is mamba-architecture free to use?
- Yes. mamba-architecture is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
- Where does mamba-architecture come from?
- mamba-architecture ships inside Orchestra-Research/AI-Research-SKILLs, a repository that contains 41 catalogued skills in total. The repository's 11,807 GitHub stars apply to that whole collection, not to this skill on its own.
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