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license: mit
title: rrchat AI
sdk: static
emoji: ⚡
colorFrom: red
colorTo: indigo
pinned: true
short_description: Main card of rrchat!
---
<div align="center">
<img src="https://huggingface.co/rrchat/Viper-9B/resolve/main/rrgen1banner.png" alt="rrchat AI Banner" width="100%" style="border-radius: 12px; margin-bottom: 14px; box-shadow: 0 4px 20px rgba(0,0,0,0.15);">
# rrchat AI
**Open-source compact reasoning models & private mobile-ready local AI**
[](https://github.com/leftik1/rrchat)
[](https://huggingface.co/rrchat)
[](https://github.com/ggerganov/llama.cpp)
[](https://www.apache.org/licenses/LICENSE-2.0)
</div>
---
### 🌐 Overview
**rrchat AI** is an open-source initiative focused on high-efficiency, private local AI: combining compact bilingual (RU/EN) reasoning models with native mobile interfaces.
Our goal is to bring sovereign intelligence directly into your workflow — zero cloud telemetry, maximum throughput on consumer hardware, and seamless orchestration between mobile devices and local GPU workstations.
---
### 🧠 Models: RR-Gen1 Series
The **RR-Gen1** lineup spans from ultra-fast 1.7B edge assistants to a 9B agentic flagship, optimized for agentic tool use, mathematical reasoning, and competitive coding:
| Model | Size / Active | Base Architecture | Primary Strengths | Recommended VRAM | Weights & GGUF |
| :--- | :---: | :---: | :--- | :---: | :---: |
| **Viper-9B** *(Flagship)* | 9B | Qwen3.5-9B | Competitive Coding (LCB 33%), Agentic Tool Calling, Math CoT, R-Tuning Honesty | ~8–12 GB | [Base](https://huggingface.co/rrchat/Viper-9B) · [GGUF](https://huggingface.co/rrchat/Viper-9B-GGUF) |
| **Cerberus-E4B** | 4B (7.5B Total) | Gemma 4-E4B | Balanced Multi-Task Reasoning, Native Gemma Tool Schemas, Multimodal | ~4–8 GB | [Base](https://huggingface.co/rrchat/Cerberus-E4B) · [GGUF](https://huggingface.co/rrchat/Cerberus-E4B-GGUF) |
| **Mercury-1.7B** | 1.7B | LFM3-VL-2B | Extreme Speed (~180–200 t/s), Linear Attention + Short-Conv, SigLIP Vision | ~2–4 GB | [Base](https://huggingface.co/rrchat/Mercury-1.7B) · [GGUF](https://huggingface.co/rrchat/Mercury-1.7B-GGUF) |
| **Mercury-Acad-1.7B** | 1.7B | LFM3-VL-2B | Academic & Scientific Reasoning, Mathematical CoT, STEM Domain Specialist | ~2–4 GB | [Base](https://huggingface.co/rrchat/Mercury-Acad-1.7B) · [GGUF](https://huggingface.co/rrchat/Mercury-Acad-1.7B-GGUF) |
#### 🔬 Lineup Highlights
* 🐍 **Viper-9B**: The flagship for software engineering and complex reasoning. Demonstrates +14% absolute gain on LiveCodeBench v6, 84.7% on MBPP+, and calibrated factual honesty without confident hallucinations.
* 🐺 **Cerberus-E4B**: Efficient mid-weight specialist built on Google's Gemma 4 backbone, excelling in multi-turn tool interaction and structured bilingual reasoning.
* ⚡ **Mercury-1.7B**: Sub-2B powerhouse powered by Liquid AI's hybrid linear attention and causal depthwise convolutions, delivering desktop-class reasoning at up to 200 tokens/sec on edge hardware.
* 🎓 **Mercury-Acad-1.7B**: Tailored for mathematical research, paper comprehension, and STEM problem solving with dual-mode explicit reasoning (`<think>`).
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### 📱 Client: [rrchat](https://github.com/leftik1/rrchat)
**rrchat** is a privacy-first mobile client designed to pair your phone directly with your PC or local server running `llama.cpp`, `llama-server`, or `Ollama`:
* 🔒 **100% Local & Sovereign:** Direct peer-to-peer connection over your local network/VPN. No middleman servers, no tracking, zero cloud lock-in.
* 👁️ **Full Multimodal Workflow:** Integrated camera vision, audio voice notes transcription, and document analysis.
* 🌐 **Agentic Web Search:** Privacy-preserving web exploration powered by local models without vendor profiling.
* ⚡ **Instant Pairing:** One-tap connect via local IP / QR code with automatic model detection and context management.
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<div align="center">
<sub>Built by <a href="https://huggingface.co/rrchat">rrchat</a> · Empowering sovereign open-source intelligence</sub>
</div> |