This is very exciting, thanks for sharing Mike! I can't wait to try the dev
trial!

Can you comment on whether you expect this to rely on closed source
components / models? What is the thinking regarding a public eval suite?

Thanks,
   Rick

On Thu, Oct 1, 2026 at 1:04 PM Mike Wasserman <[email protected]> wrote:

> Contact emails
>
> [email protected], [email protected]
>
> Explainer
>
> https://github.com/explainers-by-googlers/decisions-api
>
> Specification
>
> No information provided
>
> Summary
>
> Provides high-speed, deterministic semantic decision-making directly on
> the user's device as a built-in AI capability.
>
> Unlike open-ended generative language models (such as the Prompt API) that
> decode text token-by-token over hundreds or thousands of milliseconds, the 
> Decisions
> API (window.DecisionModel) evaluates natural language input text against
> a structured set of questions and candidate options in a single forward
> pass using logit scoring. This delivers micro-latency evaluations (tens
> or low hundreds of milliseconds on typical consumer laptop CPUs and GPUs)
> while outputting calibrated confidence values.
>
> This brings non-autoregressive "System 1" decision models (e.g. Jev
> <https://typesafe.ai/blog/introducing-system-one-models-and-jev>, Laya
> <https://huggingface.co/convaiinnovations/laya>, Kev
> <https://github.com/jaredpalmer/kev>, Open-Jev
> <https://github.com/kyegomez/open-jev>) natively into the web platform,
> providing developers with a pragmatic, zero-marginal-cost "Semantic If"
> primitive for real-time client-side routing, interactive input guardrails,
> and adaptive user interfaces.
>
> Blink component
>
> Blink>AI
> <https://issues.chromium.org/issues?q=customfield1222907:%22Blink%3EAI%22>
>
> Web Feature ID
>
> Missing feature
>
> Motivation
>
> Web applications and agentic workflows increasingly need to make fast,
> structured decisions over unstructured input and page state: Which search
> filters match this natural-language query? Which UI action or tool fulfills
> the user's goal? Would this draft trigger a moderation review or miss key
> details before submission? What does this page section or form field
> represent? [1]
>
> Without a built-in decision primitive, developers are forced to choose
> between several suboptimal alternatives [2]:
>
>
>    1.
>
>    Brittle Heuristics: Keyword rules and regular expressions that are
>    fast and local, but break on phrasing variations, typos, and multilingual
>    input.
>    2.
>
>    Bespoke Model Selection & Training Tax: For most web products,
>    curating training data, evaluating models, integrating runtimes, and
>    bundling multi-megabyte model weights is a prohibitive operational hurdle.
>    Users also face downsides of duplicating network and storage costs, and
>    unmanaged resource contention across origins.
>    3.
>
>    Cloud AI Endpoints: Capable, but introduces hundreds of milliseconds
>    network round trips, triggers privacy tradeoffs by transmitting user drafts
>    off-device, and incur recurring or high-frequency cloud / server costs.
>    4.
>
>    Generative LLMs (LanguageModel): Autoregressively generating
>    structured JSON via client-side LLMs is 10–50x heavier than necessary,
>    consumes significant battery/RAM, and lacks calibrated option 
> probabilities.
>
>
> Recent advancements demonstrate that compact, non-autoregressive decision
> models can evaluate candidate choices in tens of milliseconds with
> calibrated confidence distributions. We believe Built-in AI has a natural
> role to play: by offering a platform-level decision engine, we can make
> fast semantic branching an ubiquitous primitive. Web applications gain
> instant access to binary verification, categorical routing, and ordinal
> scoring tasks with amortized overheads, on-device privacy, and efficient
> hardware utilization.
>
> This prototype phase aims to confirm whether the community's enthusiasm
> translates into concrete web production use cases and architectural
> viability.
>
> [1]: https://github.com/explainers-by-googlers/decisions-api#use-cases
>
> [2]:
> https://github.com/explainers-by-googlers/decisions-api#considered-alternatives
>
>
> Initial public proposal
>
> https://github.com/webmachinelearning/proposals/issues/20
>
> Goals for experimentation
>
> For the initial DevTrial behind chrome://flags/#decisions-api, we are
> intentionally starting with a minimal viable surface focused on common
> decision evaluations. This allows us to validate core latency, ergonomics,
> and accuracy on key client-side routing scenarios first.
>
> We will use early developer and ecosystem feedback to iterate on the API
> shape, optimize runtime performance and model quality, and determine which
> additional capabilities warrant graduation into subsequent milestones.
>
> Requires code in //chrome?
>
> True
>
> Tracking bug
>
> https://issues.chromium.org/issues/568193538
>
> Measurement
>
> Use counters will track API adoption: DecisionModel_Availability,
> DecisionModel_Create, and DecisionModel_Evaluate.
>
> Estimated milestones
>
> 157
>
> Link to entry on the Chrome Platform Status
>
> https://chromestatus.com/feature/5155080092385280?gate=5985020782182400
>
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