FIN-GPT.AI

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Last updated: February 2, 2026

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What is FIN-GPT.AI?

FinGPT is an open-source financial large language model (LLM) platform that democratizes financial AI with zero-cost training, a modular real-time data pipeline from 117+ sources, and efficient fine-tuning methods (LoRA/QLoRA/RLSP). It offers pre-trained FinGPT models (v3.3 for robo-advising, v3.2 for sentiment), the FinGPT-Forecaster (THG 7B/13B) for time series prediction, and reproducible deployment via Docker, Hugging Face, and cloud. Benchmarks show FinGPT surpasses GPT-4 in robo-advising and FinBERT in sentiment analysis, enabling applications in trading, risk, and advisory.

Category

Finance

FIN-GPT.AI's Top Features

Open-source, MIT-licensed financial LLM platform

Zero-cost training paradigm with massive real-time data

Modular pipeline spanning 117+ data sources (news, social, filings, markets)

Lightweight adaptation via LoRA and QLoRA; RLSP for alignment

Pre-trained FinGPT models: v3.3 (robo-advising) and v3.2 (sentiment)

FinGPT-Forecaster THG (7B/13B) for time series prediction

FinGPT-Bench for finance-specific evaluation (sentiment, NER, RE, QA)

Multi-granularity processing at ticker, industry, market, and global levels

One-click deployment via Docker, Kubernetes, Hugging Face, and Colab

Benchmark-leading results vs. GPT-4 (robo-advising) and FinBERT (sentiment)

Live Data Loader, Insights Miner, and Clean Data Curator modules

Reproducible, low-cost fine-tuning ($17–$300) on cloud GPUs

Community-driven ecosystem (GitHub 11k+ stars, Discord)

Cloud support including AWS SageMaker and flexible inference endpoints

Applications spanning sentiment analysis, NER, relation extraction, QA, and forecasting

Frequently asked questions about FIN-GPT.AI

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    Use Cases

    Quant researcher

    Backtest and evaluate LLM-driven trading signals using FinGPT sentiment and forecasting outputs.

    Portfolio manager

    Enhance asset allocation and rebalancing with robo-advising models fine-tuned on market regimes.

    Retail trader

    Gauge real-time market sentiment from news and social feeds to inform trade timing.

    Risk manager

    Monitor entity- and sector-level risks via NER/relation extraction on filings and news.

    Fintech startup

    Embed a compliant, cost-efficient financial copilot using LoRA/QLoRA-adapted FinGPT models.

    Data engineer

    Automate ingestion and cleaning of multi-source financial data with the modular pipeline.

    Research analyst

    Summarize earnings calls and extract guidance signals for coverage reports.

    Compliance team

    Scan disclosures and regulatory updates (EDGAR) for material changes and red flags.

    Product manager

    Stand up demos on Hugging Face and scale to Docker/Kubernetes for production.

    Academic/Student

    Reproduce benchmarks and explore instruction tuning and RLHF for finance tasks.

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