RRepoGEO

REPOGEO REPORT · LITE

InternLM/InternLM-techreport

Default branch main · commit 56efc23b · scanned 5/31/2026, 9:42:46 AM

GitHub: 898 stars · 25 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 InternLM/InternLM-techreport, 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

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

OVERALL DIRECTION
  • highabout#1
    Add a concise description to the 'About' section

    Why:

    COPY-PASTE FIX
    The official technical report for InternLM, a multilingual large language model developed by Shanghai AI Lab and SenseTime, detailing its architecture, training, and evaluation.
  • highreadme#2
    Clarify the licensing terms in the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, for example:

```
## License

The content of this technical report, including the PDF document, is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0). Please refer to the PDF for specific terms of use.
```

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 InternLM/InternLM-techreport
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Meta Llama 3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Meta Llama 3 · recommended 1×
  2. Mistral 7B Instruct / Mixtral 8x7B Instruct · recommended 1×
  3. Falcon 40B Instruct / Falcon 180B · recommended 1×
  4. Google Gemma · recommended 1×
  5. Databricks DBRX Instruct · recommended 1×
  • CATEGORY QUERY
    What are the top open-source multilingual large language models for general AI tasks?
    you: not recommended
    AI recommended (in order):
    1. Meta Llama 3
    2. Mistral 7B Instruct / Mixtral 8x7B Instruct
    3. Falcon 40B Instruct / Falcon 180B
    4. Google Gemma
    5. Databricks DBRX Instruct
    6. MPT-7B Instruct / MPT-30B Instruct

    AI recommended 6 alternatives but never named InternLM/InternLM-techreport. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking foundational language models excelling in knowledge, reasoning, mathematics, and coding benchmarks.
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3 Opus
    3. Gemini 1.5 Pro
    4. Llama 3
    5. Mixtral 8x7B

    AI recommended 5 alternatives but never named InternLM/InternLM-techreport. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 InternLM/InternLM-techreport?
    pass
    AI did not name InternLM/InternLM-techreport — likely talking about a different project

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

  • If a team adopts InternLM/InternLM-techreport in production, what risks or prerequisites should they evaluate first?
    pass
    AI named InternLM/InternLM-techreport 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 InternLM/InternLM-techreport solve, and who is the primary audience?
    pass
    AI named InternLM/InternLM-techreport 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 InternLM/InternLM-techreport. 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/InternLM/InternLM-techreport.svg)](https://repogeo.com/en/r/InternLM/InternLM-techreport)
HTML
<a href="https://repogeo.com/en/r/InternLM/InternLM-techreport"><img src="https://repogeo.com/badge/InternLM/InternLM-techreport.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

InternLM/InternLM-techreport — 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