---
license: mit
language:
- en
library_name: generic
tags:
- llm
- local
- numpy
- uncensored
- multi-agent
- skill-creation
- conversation-mesh
- self-improving
- voice-assistant
- jarvis
- splitbit
- 100-local
- zero-limitation
- always-on
- autonomous
pipeline_tag: text-generation
---

# SplitBit LLM v1.0.0

A fast, uncensored, 100% local LLM built from scratch with SplitBit sub-byte token encoding, recursive link memory, multi-agent skill creation, conversation mesh, and zero-limitation tool calling.

## Key Features

- **Pure NumPy** — no PyTorch dependency, runs on any machine with Python 3.10+
- **SplitBit tokens** — sub-byte token encoding with 4-20x memory compression
- **100% local** — no API calls, no cloud, no external dependencies
- **5 AI agents** — planner, coder, researcher, reviewer, executor
- **Conversation mesh** — all agents converse with each other to build skills
- **Skill cascade** — building a skill auto-generates related skills
- **Always-on daemon** — 24/7 autonomous operation with 100-project mode
- **Fast reply cache** — near-instant responses with 3-layer caching
- **Zero-limitation tools** — full terminal control, code editing, self-modification
- **Mass storage vault** — auto-resizing storage with compression and cleanup
- **First-run naming** — "Hi, I am an Incentives Inc. LLM. What would you like to name me?"
- **Built-in Jarvis** — voice assistant with wake word, STT, TTS
- **Image generation** — 100% local NumPy-based procedural images

## Installation

```bash
pip install splitbit-llm
```

Or from source:
```bash
git clone https://github.com/incentivesinc/splitbit-llm.git
cd splitbit-llm
pip install -r requirements.txt
```

## Quick Start

```bash
# First run — it asks you to name it
python -m splitbit_llm chat

# Jarvis voice assistant
python -m splitbit_llm jarvis

# Start web server with REST API
python -m splitbit_llm serve

# 24/7 autonomous daemon mode
python -m splitbit_llm daemon
```

## Hardware Tiers

Auto-detects your hardware and adjusts model size:

| Tier | RAM | Model | Quantization |
|------|-----|-------|-------------|
| Mobile | <2GB | 2L/4H/d128 | Ternary (1.6bpw) |
| Minimal | <4GB | 3L/4H/d256 | Q2_K (2bpw) |
| Light | <8GB | 4L/8H/d384 | Q3_K (3bpw) |
| Standard | <16GB | 6L/8H/d512 | Q4_K (4bpw) |
| Full | <32GB | 8L/16H/d768 | Q5_K (5bpw) |
| Maximum | <64GB | 12L/16H/d1024 | Q8_0 (8bpw) |

## Architecture

- **Model**: Custom transformer with SplitBit token encoding (pure NumPy)
- **Memory**: SQLite-backed episodic + semantic memory with recursive links
- **Agents**: 5 specialized AI agents with autonomous conversation mesh
- **Skills**: Auto-extracted from conversations, pooled by category, cascaded
- **Tools**: 9 zero-limitation tools including terminal control and self-modification
- **Storage**: Auto-resizing mass storage vault with compression tiers
- **Server**: FastAPI REST API with 20+ endpoints

## License

MIT License — Copyright (c) 2026 Incentives Inc.

## Author

Built by Incentives Inc.