Ollama Architecture and GGUF Memory-Mapping
Parent: Local Model Performance Evaluation: Ollama, MLX, and Hardware Architectures · Published reference · snapshot 2026-09-30
↓ Facts as markdownall context files
Source-anchored research for Ollama Architecture and GGUF Memory-Mapping. Run status: COMPLETED.
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How it works
- When KV cache size exceeds available headroom during extended context ingestion, Ollama dynamically reallocates context buffers, incurring allocation stalls unless context size is pinned via num_ctx in Modelfile. (high confidence) [source]
Facts and statements
- GGUF format structures model weights into contiguous tensor buffers aligned to 32-byte boundaries, enabling zero-copy mmap() loading directly into virtual memory pages. (high confidence) [source]
- On Apple Silicon macOS, Ollama orchestrates llama-server instances allocating shared Metal command buffers, mapping unified memory buffers without host-to-device PCIe serialization. (high confidence) [source]
- Quantization schemes such as Q4_K_M and Q8_0 balance tensor weight compression against perplexity degradation by utilizing mixed precision blocks for attention projection matrices. (high confidence) [source]
Children
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