diff --git a/docs/GGML-llama.cpp-models.md b/docs/GGML-llama.cpp-models.md
deleted file mode 100644
index bcf3c046..00000000
--- a/docs/GGML-llama.cpp-models.md
+++ /dev/null
@@ -1,53 +0,0 @@
-# Using llama.cpp in the web UI
-
-## Setting up the models
-
-#### Pre-converted
-
-Place the model in the `models` folder, making sure that its name contains `ggml` somewhere and ends in `.bin`.
-
-#### Convert LLaMA yourself
-
-Follow the instructions in the llama.cpp README to generate the `ggml-model.bin` file: https://github.com/ggerganov/llama.cpp#usage
-
-## GPU acceleration
-
-Enabled with the `--n-gpu-layers` parameter. 
-
-* If you have enough VRAM, use a high number like `--n-gpu-layers 200000` to offload all layers to the GPU. 
-* Otherwise, start with a low number like `--n-gpu-layers 10` and then gradually increase it until you run out of memory.
-
-To use this feature, you need to manually compile and install `llama-cpp-python` with GPU support.
-
-#### Linux
-
-```
-pip uninstall -y llama-cpp-python
-CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip install llama-cpp-python --no-cache-dir
-```
-
-#### Windows
-
-```
-pip uninstall -y llama-cpp-python
-set CMAKE_ARGS="-DLLAMA_CUBLAS=on"
-set FORCE_CMAKE=1
-pip install llama-cpp-python --no-cache-dir
-```
-
-#### macOS
-
-```
-pip uninstall -y llama-cpp-python
-CMAKE_ARGS="-DLLAMA_METAL=on" FORCE_CMAKE=1 pip install llama-cpp-python --no-cache-dir
-```
-
-Here you can find the different compilation options for OpenBLAS / cuBLAS / CLBlast: https://pypi.org/project/llama-cpp-python/
-
-## Performance
-
-This was the performance of llama-7b int4 on my i5-12400F (cpu only):
-
-> Output generated in 33.07 seconds (6.05 tokens/s, 200 tokens, context 17)
-
-You can change the number of threads with `--threads N`.
diff --git a/docs/llama.cpp.md b/docs/llama.cpp.md
new file mode 100644
index 00000000..07d3a1d8
--- /dev/null
+++ b/docs/llama.cpp.md
@@ -0,0 +1,42 @@
+# llama.cpp
+
+llama.cpp is the best backend in two important scenarios:
+
+1) You don't have a GPU.
+2) You want to run a model that doesn't fit into your GPU.
+
+## Setting up the models
+
+#### Pre-converted
+
+Download the ggml model directly into your `text-generation-webui/models` folder, making sure that its name contains `ggml` somewhere and ends in `.bin`. It's a single file.
+
+`q4_K_M` quantization is recommended.
+
+#### Convert Llama yourself
+
+Follow the instructions in the llama.cpp README to generate a ggml: https://github.com/ggerganov/llama.cpp#prepare-data--run
+
+## GPU acceleration
+
+Enabled with the `--n-gpu-layers` parameter. 
+
+* If you have enough VRAM, use a high number like `--n-gpu-layers 1000` to offload all layers to the GPU. 
+* Otherwise, start with a low number like `--n-gpu-layers 10` and then gradually increase it until you run out of memory.
+
+This feature works out of the box for NVIDIA GPUs. For other GPUs, you need to uninstall `llama-cpp-python` with
+
+```
+pip uninstall -y llama-cpp-python
+```
+
+and then recompile it using the commands here: https://pypi.org/project/llama-cpp-python/
+
+#### macOS
+
+For macOS, these are the commands:
+
+```
+pip uninstall -y llama-cpp-python
+CMAKE_ARGS="-DLLAMA_METAL=on" FORCE_CMAKE=1 pip install llama-cpp-python --no-cache-dir
+```