RRepoGEO

REPOGEO REPORT · LITE

MetaGLM/FinGLM

Default branch main · commit ff48a9dc · scanned 5/26/2026, 1:53:04 AM

GitHub: 2,232 stars · 314 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface MetaGLM/FinGLM, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening sentence to clearly state it's a financial LLM solution

    Why:

    CURRENT
    📃 **FinGLM**: 致力于构建一个开放的、公益的、持久的金融大模型项目，利用开源开放来促进「AI+金融」。
    COPY-PASTE FIX
    📃 **FinGLM**: 一个开放、公益、持久的**金融大语言模型（FinLLM）项目及解决方案**，旨在通过开源开放深度促进「AI+金融」的融合与应用。
  • hightopics#2
    Update repository topics with specific financial AI terms and correct spelling

    Why:

    CURRENT
    chatglm, finacial, gpt, llama, llm
    COPY-PASTE FIX
    chatglm, financial-llm, fintech, ai-in-finance, large-language-models, llm
  • mediumlicense#3
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a LICENSE file (e.g., Apache-2.0) to the root of the repository.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface MetaGLM/FinGLM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
pytorch/pytorch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. pytorch/pytorch · recommended 2×
  2. huggingface/transformers · recommended 1×
  3. Lightning-AI/lightning · recommended 1×
  4. tensorflow/tensorflow · recommended 1×
  5. keras-team/keras · recommended 1×
  • CATEGORY QUERY
    How to build a large language model for financial analysis and applications?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. PyTorch (pytorch/pytorch)
    3. PyTorch Lightning (Lightning-AI/lightning)
    4. TensorFlow (tensorflow/tensorflow)
    5. Keras (keras-team/keras)
    6. JAX (google/jax)
    7. Flax (google/flax)
    8. Haiku (deepmind/dm-haiku)
    9. DeepSpeed (microsoft/DeepSpeed)
    10. OpenAI API
    11. LangChain (langchain-ai/langchain)

    AI recommended 11 alternatives but never named MetaGLM/FinGLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking open-source resources for developing AI models specifically tailored for financial industries.
    you: not recommended
    AI recommended (in order):
    1. QuantConnect (Lean) (QuantConnect/Lean)
    2. Zipline (quantopian/zipline)
    3. TensorFlow / Keras
    4. PyTorch (pytorch/pytorch)
    5. Scikit-learn (scikit-learn/scikit-learn)
    6. Arch (bashtage/arch)
    7. OpenBB Terminal (OpenBB-finance/OpenBBTerminal)

    AI recommended 7 alternatives but never named MetaGLM/FinGLM. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of MetaGLM/FinGLM?
    pass
    AI named MetaGLM/FinGLM explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts MetaGLM/FinGLM in production, what risks or prerequisites should they evaluate first?
    pass
    AI named MetaGLM/FinGLM explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo MetaGLM/FinGLM solve, and who is the primary audience?
    pass
    AI named MetaGLM/FinGLM explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of MetaGLM/FinGLM. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/MetaGLM/FinGLM.svg)](https://repogeo.com/en/r/MetaGLM/FinGLM)
HTML
<a href="https://repogeo.com/en/r/MetaGLM/FinGLM"><img src="https://repogeo.com/badge/MetaGLM/FinGLM.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

MetaGLM/FinGLM — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite