REPOGEO REPORT · LITE
open-mmlab/Multimodal-GPT
Default branch main · commit 9c73e47a · scanned 6/30/2026, 6:58:24 PM
GitHub: 1,511 stars · 129 forks
Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
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 open-mmlab/Multimodal-GPT, 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.
- highreadme#1Reposition the README H1 and opening paragraph to clarify purpose
Why:
CURRENT# 🤖 Multi-modal GPT Train a multi-modal chatbot with visual and language instructions!
COPY-PASTE FIX# 🤖 Multimodal-GPT: A Training Framework for Vision-Language Instruction Tuning Multimodal-GPT is an open-source framework and model for training multimodal large language models (LLMs) that understand and generate content based on both visual and language instructions. Built upon OpenFlamingo, it enables researchers and developers to efficiently fine-tune LLMs using diverse visual instruction data (VQA, Image Captioning, Visual Reasoning, Text OCR, Visual Dialogue) and language-only instruction data.
- mediumtopics#2Add more specific topics to improve categorization
Why:
CURRENTflamingo, gpt, gpt-4, llama, multimodal, transformer, vision-and-language
COPY-PASTE FIXflamingo, gpt, gpt-4, llama, multimodal, transformer, vision-and-language, multimodal-llm-training, instruction-tuning, vision-language-model, research-framework
- lowhomepage#3Add a project homepage URL
Why:
COPY-PASTE FIXhttps://openmmlab.com/Multimodal-GPT
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.
- OpenAI GPT-4V · recommended 1×
- Google Gemini · recommended 1×
- Llama 3 · recommended 1×
- haotian-liu/LLaVA · recommended 1×
- adept/fuyu-8b · recommended 1×
- CATEGORY QUERYHow can I build a chatbot that understands both images and text?you: not recommendedAI recommended (in order):
- OpenAI GPT-4V
- Google Gemini
- Llama 3
- LLaVA (haotian-liu/LLaVA)
- Fuyu-8B (adept/fuyu-8b)
- Microsoft Copilot
- Hugging Face Transformers (huggingface/transformers)
- BLIP-2
- InstructBLIP
- MiniGPT-4 (Vision-CAIR/MiniGPT-4)
AI recommended 10 alternatives but never named open-mmlab/Multimodal-GPT. This is the gap to close.
Show full AI answer
- CATEGORY QUERYLooking for a framework to train large language models with visual instruction data.you: not recommendedAI recommended (in order):
- Hugging Face Transformers
- PyTorch Lightning
- DeepSpeed
- JAX
- Flax
- TensorFlow
- Keras
AI recommended 7 alternatives but never named open-mmlab/Multimodal-GPT. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
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 open-mmlab/Multimodal-GPT?passAI did not name open-mmlab/Multimodal-GPT — 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 open-mmlab/Multimodal-GPT in production, what risks or prerequisites should they evaluate first?passAI named open-mmlab/Multimodal-GPT 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 open-mmlab/Multimodal-GPT solve, and who is the primary audience?passAI named open-mmlab/Multimodal-GPT explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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open-mmlab/Multimodal-GPT — 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