GGUF files store all data in little-endian. On big-endian systems (AIX, z/OS), llama.cpp detects the mismatch and fails. This pre-converted model works directly.

Model Details

Field	Value
Parameters	1.5B
Architecture	Qwen2 transformer, 28 layers
Quantization	Q4_K_M
Context length	131,072 tokens
File	`DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M-be.gguf` (1.04 GB)
Endianness	Big-endian
Source	deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B

Note: Reasoning-focused model (chain-of-thought), distilled from DeepSeek-R1.

Performance on IBM POWER9 (AIX 7.3)

Tested at 16 threads, SMT-2:

Generation: 15.45 tok/s
Prompt processing: 7.59 tok/s

Quick Start (AIX)

bash

git clone https://gitlab.com/librepower/llama-aix.git
cd llama-aix
./scripts/fetch_upstream.sh && ./scripts/build_aix_73.sh
wget https://huggingface.co/librepowerai/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M-BE/resolve/main/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M-be.gguf
./build/bin/llama-simple -m DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M-be.gguf -n 256 -t 16 "Your prompt"

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librepowerai/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M-BE

DeepSeek-R1-Distill-Qwen-1.5B Q4_K_M — Big-Endian

Why Big-Endian?

Model Details

Performance on IBM POWER9 (AIX 7.3)

Quick Start (AIX)

Related

librepowerai/
DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M-BE