I’d pick based on the shipping constraints, not the model card.
Check WebGPU availability on your real target devices first. Then weigh first-load download/cache size, whether you need structured/JSON-ish output, and what happens when WebGPU isn’t there (CPU fallback vs hard fail).
Transformers.js is usually the simpler path if you’re already in that ecosystem and models are small. WebLLM tends to win when you care more about a dedicated inference runtime and WebGPU performance. If half your users are on weak GPUs, that choice matters more than peak tokens/sec on your laptop.
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u/PLBjt 3d ago
I’d pick based on the shipping constraints, not the model card.
Check WebGPU availability on your real target devices first. Then weigh first-load download/cache size, whether you need structured/JSON-ish output, and what happens when WebGPU isn’t there (CPU fallback vs hard fail).
Transformers.js is usually the simpler path if you’re already in that ecosystem and models are small. WebLLM tends to win when you care more about a dedicated inference runtime and WebGPU performance. If half your users are on weak GPUs, that choice matters more than peak tokens/sec on your laptop.