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README.md

@@ -1,19 +1,47 @@
-# sd-cli - multi-arch stable-diffusion.cpp builds (incl. Blackwell)
+---
+license: mit
+tags:
+- stable-diffusion
+- stable-diffusion-cpp
+- cuda
+- blackwell
+- ggml
+---
+# sd-cli — multi-arch stable-diffusion.cpp builds (incl. Blackwell)
 
 Prebuilt `sd-cli` binaries from leejet/stable-diffusion.cpp @ `master-656-0e4ee04`,
-plus the build recipe. Two CUDA variants, both carrying `sm_120` (Blackwell):
+plus the build recipe. Two CUDA variants, each a fat binary covering every NVIDIA
+GPU architecture from its floor up through Blackwell.
 
-| binary        | toolkit | arches (real + PTX)                  | driver floor  |
-|---------------|---------|--------------------------------------|---------------|
-| `sd-cli-cu12` | 12.8    | 70 75 80 86 89 90 100 120 (+120 PTX) | sm_70 (Volta) |
-| `sd-cli-cu13` | 13.0    | 75 80 86 89 90 100 120 (+120 PTX)    | sm_75 (Turing)|
+## Supported GPU architectures
 
-Download from **Releases**. Dynamically linked against the CUDA runtime
-(cudart/cublas/nccl) - same as upstream - so run on a box where those are on
-the loader path (a PyTorch/CUDA image, or `pip install nvidia-cuda-runtime-cu12
-nvidia-cublas-cu12 nvidia-nccl-cu12` + LD_LIBRARY_PATH). Build it yourself via
-the included Dockerfiles + `build-and-validate-sd-cli.sh`.
+| SM     | Architecture   | Example GPUs                          | cu12 | cu13 |
+|--------|----------------|---------------------------------------|:----:|:----:|
+| sm_70  | Volta          | Tesla V100, Titan V                   |  yes |  no  |
+| sm_75  | Turing         | RTX 20-series, GTX 16-series, T4      |  yes |  yes |
+| sm_80  | Ampere (DC)    | A100, A30                             |  yes |  yes |
+| sm_86  | Ampere         | RTX 30-series, A40, A10, A2000        |  yes |  yes |
+| sm_89  | Ada Lovelace   | RTX 40-series, L4, L40S               |  yes |  yes |
+| sm_90  | Hopper         | H100, H200, GH200                     |  yes |  yes |
+| sm_100 | Blackwell (DC) | B100, B200, GB200                     |  yes |  yes |
+| sm_120 | Blackwell      | RTX 50-series, RTX PRO 6000 Blackwell |  yes |  yes |
+
+Both binaries also embed sm_120 **PTX** (virtual arch), so they JIT-forward onto
+future architectures. Use **cu12** for older drivers / Volta; **cu13** for
+CUDA-13 hosts (Volta was dropped upstream in CUDA 13).
+
+## Usage
+
+Download from the **Files** tab (here) or **Releases** (GitHub). Dynamically
+linked against the CUDA runtime (cudart/cublas/nccl) — same as upstream — so run
+on a box where those libs are on the loader path (a PyTorch/CUDA image, or
+`pip install nvidia-cuda-runtime-cu12 nvidia-cublas-cu12 nvidia-nccl-cu12` +
+`LD_LIBRARY_PATH`).
+
+    sd-cli-cu12 -m model.gguf -p "a lovely cat" -o out.png
+
+Build it yourself via the included Dockerfiles + `build-and-validate-sd-cli.sh`.
 
 ## License
 Build recipe: MIT (see LICENSE). Binaries derive from stable-diffusion.cpp and
-ggml, both MIT - see NOTICE.
+ggml, both MIT — see NOTICE.