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AI in the browser

The technical and practical side of running AI on your own device — why on-device AI is private by design, what actually runs locally vs in the cloud, how AI runs in your browser with WebGPU and WebAssembly, the privacy cost of free AI tools, and whether browser AI works offline.

13 articles

  1. An AI tool being evaluated on a test bench, with real user files and probe inputs feeding in and gauges reporting quality, failure behavior, pricing risk, and export paths

    AI in the browser · Jul 15, 2026

    Evaluating AI tools before you depend on them

    A ninety-minute evaluation protocol for AI tools: score candidates on a test set built from your own work, probe failure modes on purpose, verify where processing runs, model repricing risk, and perform a real export before anything important depends on the answer.

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  2. A device and a cloud with AI workloads sorted between them: image segmentation, transcription, and small language models on the device side; frontier models and video generation on the server side

    AI in the browser · Jul 14, 2026

    What local AI can actually do in mid-2026

    A vendor-free status report on on-device AI as of mid-2026: segmentation, transcription, and small language models are genuinely local now; frontier reasoning and video generation are not, and the reasons are physics, not politics.

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  3. A large model made of high-precision numbers being compressed into a much smaller model of low-precision integers, shrinking from a download too big for a browser to one that fits

    AI in the browser · Jun 12, 2026

    Model quantization: how big AI models shrink to run in a browser

    A plain-English explanation of the technique that makes on-device AI possible: why a model’s size is the gatekeeper for running it in a browser, what a model actually is under the hood, how quantization stores its numbers in fewer bits for a roughly four-times reduction, why models tolerate the lost precision, what it costs in accuracy, and how it combines with distillation and pruning.

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  4. A two-column map of what on-device AI can do today versus where it still hits a wall

    AI in the browser · Jun 8, 2026

    What on-device AI can't do yet

    The honest edges of in-browser AI: frontier models, heavy video, tight memory, and when a fallback wins.

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  5. What AI runs on your device versus in the cloud

    AI in the browser · Jun 7, 2026

    What runs on your device vs in the cloud

    A practical guide to telling on-device AI from cloud AI, and what each implies.

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  6. How AI runs in your browser with WebGPU and WebAssembly

    AI in the browser · Jun 7, 2026

    How AI runs in your browser (WebGPU and WebAssembly, explained)

    A plain-language explainer of the browser tech that makes on-device AI fast enough to use.

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  7. Do browser AI tools work offline?

    AI in the browser · Jun 7, 2026

    Do browser AI tools work offline?

    How on-device AI tools keep working without a connection, and what still needs the network.

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  8. A bar chart comparing in-browser AI model download sizes across Fast, Balanced, Best and frontier tiers

    AI in the browser · Jun 6, 2026

    How big are in-browser AI models (and why size matters)

    Why an on-device model is tens to hundreds of megabytes — and why that download is worth it.

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  9. A user-hosted ONNX model URL loading into the browser and running with WebGPU and a WASM fallback

    AI in the browser · May 30, 2026

    Bring your own ONNX model: running your own weights in the browser

    The logical end state of on-device AI — if the computation happens on your machine, the model does not have to be ours. How BYO-ONNX works and why it exists.

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