--- title: README emoji: 🚀 colorFrom: gray colorTo: purple sdk: gradio pinned: false --- # 🚀 Big-Endian Models for IBM AIX and IBM i Welcome! This organization hosts **machine learning models adapted and validated for Big Endian architectures**, with a primary focus on: - IBM AIX on Power Systems (now with **10 LLMs ready to use**) - CPU-only inference (no GPU required) - Real enterprise environments (not toy benchmarks) Our goal is simple: > **Make modern AI usable on legendary mission-critical platforms.** No vendor lock-in. No mandatory accelerators. Just practical inference where your workloads already live. --- ## 📦 Available Models (v0.1.1 — Production Ready) **10 big-endian GGUF models**, fully tested on AIX 7.3 POWER9: | Model | Params | Speed | Size | Type | |-------|--------|-------|------|------| | **LFM2.5-1.2B-Instruct** | 1.17B | **26.9 tok/s** ⭐ Fastest | 695 MB | Instruct | | **LFM2.5-1.2B-Thinking** | 1.17B | **19.25 tok/s** ⭐ NEW | 731 MB | Reasoning | | H2O-Danube2-1.8B | 1.8B | 18.59 tok/s | 1.04 GB | Chat | | SmolLM2-1.7B-Instruct | 1.7B | 17.94 tok/s | 1.0 GB | Instruct | | DeepSeek-R1-Distill-1.5B | 1.5B | 15.45 tok/s | 1.04 GB | Reasoning | | StableLM-2-Zephyr-1.6B | 1.6B | 15.02 tok/s | 983 MB | Chat | | Qwen2.5-Coder-1.5B | 1.54B | 7.67 tok/s | 940 MB | Code | | Qwen2.5-1.5B-Instruct | 1.54B | 7.55 tok/s | 940 MB | Instruct | | Llama-3.2-1B-Instruct | 1.24B | 9.03 tok/s | 770 MB | Instruct | | TinyLlama-1.1B-Chat | 1.1B | ~18 tok/s | 638 MB | Chat | **Benchmarks**: AIX 7.3 TL4, IBM POWER9 @ 2.75 GHz, 16 threads (SMT-2), GCC 13.3.0 --- ## 🚀 Quick Start Download a model and run on AIX: ```bash # Clone and build git clone https://gitlab.com/librepower/llama-aix.git cd llama-aix ./scripts/build_aix_73.sh # Get a model (example: fastest model) mkdir -p models wget https://huggingface.co/librepowerai/LFM2.5-1.2B-Instruct-Q4_K_M-BE/resolve/main/LFM2.5-1.2B-Instruct-Q4_K_M.gguf -O models/ # Run inference export LIBPATH=$PWD/build/bin ./build/bin/llama-simple -m models/LFM2.5-1.2B-Instruct-Q4_K_M.gguf -n 256 "Your prompt" All models available at: https://huggingface.co/librepowerai --- 🔬 What you will find here Models and artifacts specifically prepared for: - Big Endian compatibility - AIX and IBM i runtime environments - CPU inference (optimized with VSX SIMD + OpenBLAS) - Minimal external dependencies v0.1.1 Optimizations: - VSX auto-vectorization: -O3 -mvsx -maltivec (+6.7% performance) - OpenBLAS BLAS backend: GEMM acceleration for attention layers - GCC 13.3.0 native build: no xlc required Typical contents: - Big-Endian converted GGUF models (Q4_K_M quantization) - BE-safe tokenizer assets - Complete build scripts and documentation - Performance benchmarks on real Power hardware Everything here has been tested on actual AIX systems — not emulators. --- ⚙️ Tooling Models here are intended to run with: - llama-aix - Full port of llama.cpp to AIX 7.3 https://gitlab.com/librepower/llama-aix - Native AIX / IBM i toolchains (GCC or IBM Open XL) - CPU inference (no GPU acceleration needed) We deliberately avoid GPU assumptions and licensing complexity. --- 🧭 Why Big Endian? Most open-source AI models today assume: - Little Endian - Linux - x86 or CUDA Enterprise reality is different. Many production systems run on: - IBM AIX or IBM i - POWER9 / POWER10 / POWER11 - Big Endian binaries - Highly regulated, long-lifecycle environments Porting models to BE is not trivial: tokenizers, SIMD paths, memory layout, third-party deps — everything matters. This repository exists to close that gap. --- 🌱 Philosophy We believe innovation is often not about new hardware — it is about unlocking what you already own. That means: - reducing infrastructure footprint - maximizing TCO - extending the life of enterprise platforms - keeping data on-prem when needed - enabling AI without massive architectural changes This is practical engineering work, driven by real use cases — not marketing slides. --- 📚 Documentation & Research - Build Guide: https://gitlab.com/librepower/llama-aix/-/blob/main/docs/BUILD_AIX_73.md - Troubleshooting: https://gitlab.com/librepower/llama-aix/-/blob/main/docs/TROUBLESHOOTING_AIX.md - VSX Research: https://gitlab.com/librepower/llama-aix/-/blob/main/docs/VSX_OPTIMIZATION_RESEARCH.md (Phase A & B complete, Phase C roadmap for v0.2) - Blog: https://sixe.eu/news/running-liquid-ais-new-model-on-ibm-aix-no-gpu-required --- 🔗 Related projects - LibrePower Open Source Initiative https://librepower.org - llama-aix (this port) https://gitlab.com/librepower/llama-aix - AIX Ports (RPM packages) https://gitlab.com/librepower/aix - llama-ibm-i https://ajshedivy.notion.site/How-to-run-LLMs-on-IBM-i-1ce662038dd180f8b59bd9cfada2815b --- ✉️ Contact hello {at} librepower.org #LibrePower — Unlocking Power Systems through open source Minimal footprint. Unmatched RAS. Better TCO. Last updated: February 18, 2026 — v0.1.1 production release with 10 models