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COBOL, z/OS performance measurement, and systems programming updates.

oLLM

By Arch Brooks on July 31, 2026 in Artificial Intelligence

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If you mean oLLM (lowercase "o"), it's a relatively new open-source project designed for running very large-context language models on modest hardware. Instead of requiring huge amounts of VRAM, it streams model weights and KV cache between your GPU, system RAM, and NVMe SSD.

Key features:

Supports 100K+ token context windows on some models.
Works with Hugging Face Transformers and PyTorch.
Uses SSD offloading rather than aggressive quantization.
Intended primarily for offline workloads like:
- analyzing large codebases
- summarizing long documents
- compliance/legal document review
- processing large log files
The tradeoff is speed—it's much slower than keeping the entire model in GPU memory.

Given your setup (Gentoo, Intel Core Ultra 9 185H with Intel Arc graphics), oLLM is not the best fit because it currently targets NVIDIA CUDA GPUs. Since you've already configured SYCL, llama.cpp, and Ollama on your Intel Arc system, you'll generally get better performance from those than from oLLM.

If you were asking about a different OLLM/oLLM project (for example, the confidential AI gateway or another tool), let me know which one and I'll cover that instead.

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