Independent research lab in Lagos.
Intelligence efficient enough to own.
We build frontier models efficient enough to run on hardware people already own.
| Model | What it is |
|---|---|
| BTL-4 | 35.1B mixture-of-experts, ~2.1B active parameters per token, 262K context |
| BTL-4 Compact | The same model in one 9.96 GB GGUF at 2.30 bits per weight, retaining 94.1% of measured full-precision behaviour (111 of 118 on a teacher-correct replay set). Runs in stock llama.cpp, Ollama, and LM Studio. |
| BTL-3 | 27B agentic coding and tool-use model |
| BTL-3 Compact | The complete text model in one 8.39 GB native GGUF |
| Macaw | 2.7B on-device macOS agent, 97 verified tools, no cloud |