I've just tried replicating this on my Pi 5 16GB, running the latest llama.cpp... and it segfaults:

    ./build/bin/llama-cli -m "models/Qwen3-30B-A3B-Instruct-2507-Q3_K_S-2.70bpw.gguf" -e --no-mmap -t 4
    ...
    Loading model... -ggml_aligned_malloc: insufficient memory (attempted to allocate 24576.00 MB)
    ggml_backend_cpu_buffer_type_alloc_buffer: failed to allocate buffer of size 25769803776
    alloc_tensor_range: failed to allocate CPU buffer of size 25769803776
    llama_init_from_model: failed to initialize the context: failed to allocate buffer for kv cache
    Segmentation fault

I'm not sure how they're running it... any kind of guide for replicating their results? It does take up a little over 10 GB of RAM (watching with btop) before it segfaults and quits.

[Edit: had to add -c 4096 to cut down the context size, now it loads]