# shawnshekari/strixite

> LLM inference engine written from scratch in HIP for AMD Strix Halo (gfx1151) and Qwen3.8-Flash-Next - ~50 tokens/s out to 492k context

## Fast Facts & Telemetry
- **Canonical URL**: https://githubrepo.cloud/repo/shawnshekari/strixite
- **GitHub Source**: https://github.com/shawnshekari/strixite
- **Global Rank**: #19,382 on GitHubRepo
- **Stars**: 62
- **Forks**: 7
- **Open Issues**: 0
- **Primary Language**: C++
- **Software License**: AGPL-3.0
- **Last Commit / Push**: Oct 18, 2026
- **Topics**: amd, hip, llm-inference, local-llm, qwen, rocm, strix-halo

## Project Overview
strixite is an open-source project written in C++: LLM inference engine written from scratch in HIP for AMD Strix Halo (gfx1151) and Qwen3.8-Flash-Next - ~50 tokens/s out to 492k context.

Engineered for speed, consistency, and developer ease, it solves common hurdles in amd, hip, llm-inference. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

## Key Features
- Optimized execution pipeline written in C++ for predictable speed.
- Zero-friction configuration with comprehensive sensible defaults out of the box.
- Cross-platform runtime support across Linux, macOS, and Windows environments.
- Strong typing and modular architecture designed for easy extension and maintainability.
- Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
- Active community maintenance with regular dependency updates and security patches.

## Installation & Quick Start
### Linux
```bash
git clone https://github.com/shawnshekari/strixite.git
cd strixite
```

### macOS
```bash
git clone https://github.com/shawnshekari/strixite.git
cd strixite
```

### Windows
```bash
git clone https://github.com/shawnshekari/strixite.git
cd strixite
```

## System Requirements & Architecture
- **Supported Platforms**: macOS, Linux, Windows
- **Runtime Dependencies**: C++20 compliant compiler (GCC 11+, Clang 13+, MSVC)
- **Architecture**: x86_64, ARM64 (Apple Silicon & Graviton)

## How It Works
strixite coordinates its core functionality through a modular C++ pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

## Production Use Cases
### Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with strixite.

### Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.

### Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.

### Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.

## Target Audience
Developers and engineering teams building with C++, seeking reliable, tested, and actively maintained tooling for production workloads.

## Strengths
- Active community backing with 60 GitHub stars and verified adoption.
- Permissive open-source distribution under the AGPL-3.0 license.
- Built in C++ for high execution speed and developer familiarity.
- Cross-platform compatibility across modern Linux, macOS, and Windows environments.
- Clean modular design allowing flexible configuration and pipeline integration.

## Considerations
- Requires familiarity with C++ and modern CLI workflows.
- Ecosystem extensions may require manual configuration depending on environment constraints.
- Active development roadmap means breaking API changes may occur across major versions.

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