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Research#llm📝 BlogAnalyzed: Dec 27, 2025 08:31

Strix Halo Llama-bench Results (GLM-4.5-Air)

Published:Dec 27, 2025 05:16
1 min read
r/LocalLLaMA

Analysis

This post on r/LocalLLaMA shares benchmark results for the GLM-4.5-Air model running on a Strix Halo (EVO-X2) system with 128GB of RAM. The user is seeking to optimize their setup and is requesting comparisons from others. The benchmarks include various configurations of the GLM4moe 106B model with Q4_K quantization, using ROCm 7.10. The data presented includes model size, parameters, backend, number of GPU layers (ngl), threads, n_ubatch, type_k, type_v, fa, mmap, test type, and tokens per second (t/s). The user is specifically interested in optimizing for use with Cline.

Key Takeaways

Reference

“Looking for anyone who has some benchmarks they would like to share. I am trying to optimize my EVO-X2 (Strix Halo) 128GB box using GLM-4.5-Air for use with Cline.”

Permalinkr/LocalLLaMA
Research#llm👥 CommunityAnalyzed: Jan 4, 2026 09:05

Using mmap to make LLaMA load faster

Published:Apr 5, 2023 15:36
1 min read
Hacker News

Analysis

The article likely discusses the use of memory mapping (mmap) to improve the loading speed of the LLaMA language model. This is a common optimization technique, as mmap allows the operating system to handle the loading of the model's weights on demand, rather than loading the entire model into memory at once. This can significantly reduce the initial loading time, especially for large models like LLaMA.
Reference

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PermalinkHacker News
Infrastructure#llm👥 CommunityAnalyzed: Jan 10, 2026 16:15

llama.cpp's Memory Usage: Hidden Realities

Published:Apr 3, 2023 16:27
1 min read
Hacker News

Analysis

The article likely explores the discrepancy between reported memory usage and actual memory consumption within llama.cpp due to the use of memory-mapped files (MMAP). Understanding this distinction is crucial for optimizing resource allocation and predicting performance in deployments.
Reference

“The article's key discussion likely centers on the impact of MMAP on how llama.cpp reports and uses memory.”

PermalinkHacker News