Electra Base Discriminator
Google's Electra Base Discriminator is a self-supervised language representation learning model that excels at distinguishing real input tokens from fake ones generated by another neural network. It is particularly effective for pre-training transformer networks with limited computational resources, achieving state-of-the-art results on the SQuAD 2.0 dataset at large scale.
Input
Output
Context
1K
Max Output
1K
Parameters
-
Technical Specifications
Input Modalities
Output Modalities
Capabilities
Loading capabilities…
More models by Google
The creator's other models in the catalog, with their context, size and license where published.
Compare it, or keep browsing
Put this model beside its alternatives on the same evidence, or go back to the full catalog.
Frequently asked questions about Electra Base Discriminator
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Electra Base Discriminator advertises a context window of 512 tokens, with a maximum output of 512 tokens in a single response. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. Electra Base Discriminator is an open-weight model released under the Apache 2.0 license, so the weights can be downloaded and self-hosted within that license's terms.
Electra Base Discriminator accepts Text and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Electra Base Discriminator is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Electra Base Discriminator is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
Google has not published a parameter count for Electra Base Discriminator, so the catalog cannot estimate its memory footprint. The capacity planner can size it from a parameter count you supply.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Aug 28, 2026
Put intelligence in the middle.
One gateway in front of every model, with your policies applied and every decision on record. Start with $5 of credit and 5,000 routing decisions a month, no card required.