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AI Atlas
ModelAnnouncedClosed / proprietary

WeatherNext 3

Google DeepMind and Google Researchfamily · WeatherNext

Open in Graph
data quality54

Updated 9 h ago · first seen 15 Sept 2026

model_01M2K1CR5YF6EKNYYX5PME5XF5

Overview

Identity

Canonical model
Yesidentity confidence: highOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
Official checkpoints
None recorded — closed weightsofficial_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
Artifacts
None recordedSeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
Provider deployments
None recorded
API aliases
NoneIdentifiers under which providers and evaluators refer to this model.
Folded evaluation variants
0Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.

Openness

Closed / proprietary— weights not available; 7 dimensions unknown.

Weights are not available; the model is reachable only through an API or a product.

  • Weights

    No

  • Inference code

    —

  • Training code

    —

  • Training data

    —

  • Dataset

    —

  • Commercial use

    —

  • Redistribution

    —

  • Derivatives

    —

dimensions marked null are unknown, not false

Key facts

Release date

Source:Google AI for Developers (Gemini API docs)T2observed 23 h agomediumLLM-extracted

Status

Source:Google AI for Developers (Gemini API docs)T2observed 23 h agomediumLLM-extracted

Version

Source:Google AI for Developers (Gemini API docs)T2observed 23 h agomediumLLM-extracted

Architecture

Architecture

Source:Google AI for Developers (Gemini API docs)T2observed 23 h agomediumLLM-extracted

Capabilities

Modalities

Modalities
NASA’s satellite-based Integrated Multi-satellite Retrievals for GPM (IMERG)dense gridded fieldsdiscrete cyclone tracksglobal precipitation reanalysis based on satellite radarlive 1-hour geostationary satellite mosaicssparse weather station observation datastation-level sparse coordinatestraditional historical analysis
Input
NASA’s satellite-based Integrated Multi-satellite Retrievals for GPM (IMERG)global precipitation reanalysis based on satellite radarlive 1-hour geostationary satellite mosaicssparse weather station observation datatraditional historical analysis
Output
dense gridded fieldsdiscrete cyclone tracksstation-level sparse coordinates

Capabilities

  • Tool calling

    Unavailable

  • Structured output

    Unavailable

  • Reasoning

    Unavailable

  • Vision

    Unavailable

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

No capability flags have been observed from a source yet — we do not infer them.

No structured attributes yet.

Versions & Artifacts0

Version history

Opennessfirst observation only

15 Sept 2026current

Statusfirst observation only

15 Sept 2026current

Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.

Artifacts 0

No artifact (checkpoint, quantisation, conversion or packaging) points to this model yet.

Change history12

Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.

Viewing AI Atlas as of 9 Sept 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.

Back to today →

WeatherNext 3 was not yet in AI Atlas on 9 Sept 2026

First seen 15 Sept 2026. Nothing is inferred backwards: no attribute is shown for dates before the first observation.
12 claims · 12 properties

Familyfamily1

Claim history for Family
ValueValid from → toStatusSourceConfidenceExtractor
WeatherNext → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Versionversion1

Claim history for Version
ValueValid from → toStatusSourceConfidenceExtractor
3 → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Release daterelease_date1

Claim history for Release date
ValueValid from → toStatusSourceConfidenceExtractor
3 Sept 2026 → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Statusstatus1

Claim history for Status
ValueValid from → toStatusSourceConfidenceExtractor
announced → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Opennessopenness1

Claim history for Openness
ValueValid from → toStatusSourceConfidenceExtractor
proprietary → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Architecturearchitecture1

Claim history for Architecture
ValueValid from → toStatusSourceConfidenceExtractor
Functional Generative Network (FGN) mesh transformer → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Modalitiesmodalities1

Claim history for Modalities
ValueValid from → toStatusSourceConfidenceExtractor
NASA’s satellite-based Integrated Multi-satellite Retrievals for GPM (IMERG), dense gridded fields, discrete cyclone tracks, global precipitation reanalysis based on satellite radar, live 1-hour geostationary satellite mosaics, sparse weather station observation data, station-level sparse coordinates, traditional historical analysis → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Input modalitiesmodalities_input1

Claim history for Input modalities
ValueValid from → toStatusSourceConfidenceExtractor
NASA’s satellite-based Integrated Multi-satellite Retrievals for GPM (IMERG), global precipitation reanalysis based on satellite radar, live 1-hour geostationary satellite mosaics, sparse weather station observation data, traditional historical analysis → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Output modalitiesmodalities_output1

Claim history for Output modalities
ValueValid from → toStatusSourceConfidenceExtractor
dense gridded fields, discrete cyclone tracks, station-level sparse coordinates → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Safety notessafety_notes1

Claim history for Safety notes
ValueValid from → toStatusSourceConfidenceExtractor
For official weather forecasts, severe weather warnings, and public safety advisories, please refer to your local meteorological agency or national weather service. → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Training data notestraining_data_notes1

Claim history for Training data notes
ValueValid from → toStatusSourceConfidenceExtractor
Trains directly on real-time observations, including live global geostationary satellite data and sparse weather station observation data, rather than numerical weather prediction (NWP) models. → currentcurrentGoogle AI for Developers (Gemini API docs)T2mediumllm

Weights availableweights_available1

Claim history for Weights available
ValueValid from → toStatusSourceConfidenceExtractor
No → currentcurrentAI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2highderived

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

Provenance

Attributed facts

12

Source tiers

T212

Freshest observation

9 h ago

Conflicts

None

Source documents 1

Source documents
SourceDocumentTypeTierLast observedSnapshots
Google AI for Developers (Gemini API docs)deepmind.google/blog/introducing-weathernext-3-our-most-advanced-and-accurate-global-weather-ai-model newsT1· Official23 h ago1

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

Data quality (54/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →