Zero Latency.
Zero Privacy Risk.
Sending every keystroke to OpenAI is distinctely 2023.
With WebGPU and highly optimized SLMs (Small Language Models like Phi-3 or Llama-3-8B-Quantized), you can build smart autocompletes that run entirely on the client's laptop.
02. WebLLM & transformers.js
Libraries like MLC-LLM (WebLLM) compile models to TVM (Tensor Virtual Machine) which can execute on the GPU via WGSL shaders. It's shockingly fast.
Deep Dive: Shader Compilation
The very first time a user visits your site, the browser must compile the WGSL shaders for their specific GPU. This takes ~5-10 seconds.
However, browsers cache these compiled shaders. The second visit? Instant startup.
messages: [ ... ]
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04. The Senior Engineer's Take
The Download Tax
The catch? The user has to download the model weights (~2GB) first.
Pattern: Use Cloud AI for the first interaction, while downloading the Local Model in the background. Once ready, switch to Local for pure speed.
Hybrid AI
The best architecture isn't 100% local. Use GPT-4 (Cloud) for complex reasoning or planning, and Phi-3 (Local) for drafting e-mails, text completion, or UI generation where latency matters most.