🧠
Internvl2 2b model by OpenGVLab
⭐ 41.3
🧠
Model

Internvl2 2b

by OpenGVLab hf-model--opengvlab--internvl2-2b
Nexus Index
41.3 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 70
R: Recency 45
Q: Quality 65
Tech Context
2 Params
4.096K Ctx
Vital Performance
1.4M DL / 30D
0.0%
Source →
Audited 41.3 FNI Score
Tiny 2B Params
4k Context
Hot 1.4M Downloads
8G GPU ~3GB Est. VRAM
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID hf-model--opengvlab--internvl2-2b
License MIT
Provider huggingface
💾

Compute Threshold

~2.8GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__opengvlab__internvl2_2b,
  author = {OpenGVLab},
  title = {Internvl2 2b Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/opengvlab/internvl2-2b}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
OpenGVLab. (2026). Internvl2 2b [Model]. Free2AITools. https://huggingface.co/opengvlab/internvl2-2b

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run internvl2-2b
🤗 HF Download
huggingface-cli download opengvlab/internvl2-2b
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
41.3
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 70
Recency (R) 45
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Internvl2 2b: Semantic (S:50), Authority (A:0), Popularity (P:70), Recency (R:45), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
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🚀 What's Next?

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⚡

Deployment Guide

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Technical Deep Dive

⚠ī¸ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source →

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
1.4MDownloads
Hub Discussions
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--opengvlab--internvl2-2b
slug
opengvlab--internvl2-2b
source
huggingface
author
OpenGVLab
license
MIT
tags
transformers, safetensors, internvl_chat, feature-extraction, internvl, custom_code, image-text-to-text, conversational, multilingual, arxiv:2312.14238, arxiv:2404.16821, arxiv:2410.16261, arxiv:2412.05271, base_model:opengvlab/internvit-300m-448px, base_model:merge:opengvlab/internvit-300m-448px, base_model:internlm/internlm2-chat-1_8b, base_model:merge:internlm/internlm2-chat-1_8b, license:mit, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
2
context length
4,096
pipeline tag
image-text-to-text
vram gb
2.8
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
1,439,784
stars
0
forks
0

Data indexed from public sources. Updated daily.