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RECOGNITION · PROGRAMMES · ECOSYSTEM · TRUST FinanceGPT Tools
FinanceGPT LQM Ecosystem

Build, verify, publish and compose quantitative models with evidence attached.

The FinanceGPT LQM ecosystem is the public surface for Large Quantitative Models: quantitative and generative financial modules with sealed training lineage, evaluation gates, Evidence Packets and governed model-supply-chain disclosure.

Explore public LQMs Read the specification
Public registry
0
published public LQMs
7
required evaluation gates
financegpt.lqm.evidence.v1
Evidence Packet schema
Category definition

LQM means quantitative model, not language model.

A governed quantitative or generative financial model module that consumes typed numeric, categorical or time-series features and emits typed, versioned quantitative evidence. It is not a language model.

Typed numeric, categorical and time-series inputs
Typed quantitative outputs and Evidence Packets
Language remains a separate QLM-selected runtime
Separation rule

A QLM language runtime may explain a verified LQM Evidence Packet, but it never receives LQM latent state and never becomes numeric authority.

Published models

Evidence-backed public LQMs

Open leaderboard
Public registry ready.

No public LQM publication has been sealed in this environment yet. Models appear here only after governed publication completes.

Builders

Train and publish through LQM Builder.

Use FinanceGPT API v2 for registration, training, evaluation, Evidence Packets, drift operations, model-hub publishing and human-governed promotion.

Developer guide
Trust

Inspect the governance boundary.

The Trust Center documents checkpoint, evaluation, Evidence Packet, model-card, ML-BOM and publication-manifest controls without conflating model access with financial authority.

LQM trust evidence