Instructions to use RiverRider/blackwindow-mlc-libs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use RiverRider/blackwindow-mlc-libs with MLC-LLM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Black Window phone model libraries
WebGPU model libraries for WebLLM, compiled for phones. They use the standard
mlc-ai/*-q4f16_1-MLC weights unchanged; only the library differs.
WebLLM's prebuilt libraries are compiled with a 1,024-token prefill chunk, and MLC plans the working buffers from that
compiled figure, so on Qwen3 about 0.6 GB sits beside the weights whatever the page asks for at runtime. An iPhone tab
is killed somewhere between 1.1 and 1.6 GB. These libraries are compiled with prefill_chunk_size=128 and
context_window_size=1024:
| library | parameters | temporary buffer | at a 1K window |
|---|---|---|---|
Qwen3-0.6B-q4f16_1_ctx1024_cs128-webgpu.wasm |
320 MB | 79 MB | ~0.5 GB |
Qwen3-1.7B-q4f16_1_ctx1024_cs128-webgpu.wasm |
923 MB | 83 MB | ~1.1 GB |
Figures are mlc_llm compile's own accounting. Built 2026-09-10 with apache/tvm e85fbb1 (2026-08-18), mlc-llm 9fa644f5
(2026-08-17), emsdk 4.0.23, for WebLLM 0.2.85 (@mlc-ai/web-runtime 0.27). Used by https://blackwindow.xyz on phones.
Use in a WebLLM ModelRecord:
{ model: "https://huggingface.co/mlc-ai/Qwen3-1.7B-q4f16_1-MLC", model_id: "Qwen3-1.7B-q4f16_1-MLC",
model_lib: "https://huggingface.co/RiverRider/blackwindow-mlc-libs/resolve/main/Qwen3-1.7B-q4f16_1_ctx1024_cs128-webgpu.wasm",
overrides: { context_window_size: 1024, prefill_chunk_size: 128 } }
Sunstone North Labs LLC · burton@sunstonenorth.com
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