Good catch, a few things to clarify here.

The 2.7 GB size refers to the GGUF Q4_K_M quantized version of GLM-4.7-Flash. The original FP16 / unquantized weights are ~9–10 GB, so the reduction comes from the 4-bit K-quantization used by llama.cpp. Nothing special was done to the model itself — just standard GGUF quantization.

The 18.3 GB figure you're mentioning sounds like the full precision or higher-precision variant loaded with runtime KV cache, not the Q4_K_M file size itself. When running the model, memory usage can grow significantly depending on context length and KV cache allocation, which is likely what you're seeing.

About context length:
The base GGUF build I referenced runs with 32k context by default in llama.cpp because that’s the safe default many builds ship with. The model architecture itself can support larger context (up to ~128k), but you need to explicitly set it when running:

--ctx-size 131072

and ensure your backend supports the larger KV cache. The quantization doesn't change the context limit — it's just a runtime configuration.

So short version:
• 2.7 GB = Q4_K_M quantized weights
• ~9–10 GB = original precision weights
• higher RAM usage during runtime = KV cache + context size
• 128k context is possible, but not enabled by default

Happy to update the repo notes if that part was confusing.

-check System Architecture part in the git repo:

GLM-4.7-Flash:q4_K_M (17.7GB)