recommendation
DCN V2
Improved Deep and Cross Network, used across many web-scale learning-to-rank systems at Google. Paper by Wang et al. (2020).
Levelvariant
Classrecommendation
Parametersnot in the notes
Contextnot in the notes
Released19 Aug 2020
Opennessunknown
Runs onnot in the notes
Statusactive
Lineage
successor
DCN (Deep and Cross Network) is the parent (successor)high confidencenotesWhere this comes from
Parent and child relations from model cards, Hugging Face base_model fields and the genealogy tables of the research notes. The tree shows two generations each way, 2 models. Confidence and evidence are the notes' own.
Identity
- Developer
- Family
- DCN (Deep and Cross Network)
- Released
- 19 Aug 2020 sourcesannouncement page
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- other
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- table
- Output
- table
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- unknown
- Licence
- not in the notes sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- not in the notes
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Industry Use Cases
No industry use case links this model.
Links
DeveloperGooglebig tech, USA
Googlebig tech, USAModelDCN V2Google, recommendation
DCN V2Google, recommendationUse CasesSuper-App Recommendation and PersonalisationRetail and LogisticsUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
GrabIn production, 6 Oct 2026Deployments of these use cases; none names this model.
GrabIn production, 6 Oct 2026Deployments of these use cases; none names this model.Organisations 1
Sources
- arxiv.org/abs/2008.13535 https://arxiv.org/abs/2008.13535
- nvidia-merlin.github.io/models/stable/models_overview.html https://nvidia-merlin.github.io/models/stable/models_overview.html
- github.com/RUCAIBox/RecBole2.0/blob/main/model_list.md https://github.com/RUCAIBox/RecBole2.0/blob/main/model_list.md
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "DCN V2", https://aurion.semai.id/models/google-dcn-v2/, records of October 2026.