Browser boot and model selection

Follows the exact JavaScript initialization sequence, default q8 model choice, stale-load protection, recovery behavior, and provenance-sidecar rendering.

Experimental
Last verified
2026-06-25 00:00 UTC
Updated
Reading time
2 minutes

Follows the exact JavaScript initialization sequence, default q8 model choice, stale-load protection, recovery behavior, and provenance-sidecar rendering.

Implementation evidence: this topic is grounded in the reviewed GGUF.MiRust.com source snapshot. It documents observed code and artifacts without claiming broad deployment, model quality, or production readiness.

Architecture topic: this page does not claim that the WordPress website implements or executes the described runtime behavior.

Boot sequence

  1. Cache required DOM nodes.
  2. Fetch and instantiate runtime/tinyrustlm.wasm.
  3. Capture exported memory and functions.
  4. Call init_runtime.
  5. Load the default tinylm16q8 route.
  6. Enable generation only after Rust accepts the artifact.

Model routes

The selector exposes TinyLM-16M q8_0, q4_0, and f32 plus tiny f32, q8, q4, BPE, and tied-output fixtures. Route keys map to fixed same-origin paths and matching .slm.manifest sidecars.

Race control

The loader tracks a sequence token so a slower previous fetch cannot overwrite a newer user selection. UI actions remain disabled during a pending load.

Provenance timing

Rust model admission happens before JavaScript fetches the sidecar. The manifest informs the operator but is not itself an input to parser admission. A future security design should verify manifest identity and artifact hash before activating the model.

Scope

This starter page defines the questions, boundaries, evidence, and failure modes that should be recorded before a capability is presented as supported.

Engineering considerations

  • Identify the source, version, target environment, and owner.
  • Separate observed values from estimates and externally reported values.
  • Record trade-offs, unsupported cases, and fallback behavior.
  • Link performance statements to a compatible benchmark methodology.

Verification questions

  • What exact artifact, revision, backend, and environment were reviewed?
  • Which assumptions could change the result?
  • Which data should be retained so another engineer can reproduce the conclusion?