# zai-org/CogVLM2

GPT4V-level open-source multi-modal model based on Llama3-8B

Repository: https://github.com/zai-org/CogVLM2
Canonical: https://ross.abutalabs.com/products/cogvlm2
Language: Python
License: Apache-2.0
License Family: permissive
Topics: cogvlm, pretrained-models, language-model, multi-modal
Last push: 2025-03-03T03:01:31+00:00

## Health v2 (maintenance only)
Score: 28/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 9, release rhythm 35, longevity 60
- inputs: {"age_days": 845, "days_push": 548, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2433, forks 162 (observed 2026-08-28T04:06:51.258288+00:00)

## What it is
CogVLM2 is an open-source multi-modal vision-language model family built on Meta-Llama-3-8B-Instruct, offering image and video understanding with up to 8K context and 1344x1344 resolution. The repository provides model weights, inference code, and demos for tasks like VQA, document understanding, and video question answering.

## Use cases
- answer questions about images with a vision-language model
- understand and summarize videos with an open-source model
- run a GPT-4V alternative locally on my own GPU
- extract text and answer questions from document images
- build a multimodal chatbot that sees images
- quantize a large vision-language model to fit in 16GB VRAM

## When to choose
- you need a self-hosted open-source alternative to GPT-4V for image or video understanding
- you want strong benchmark performance on TextVQA and DocVQA
- you need bilingual (Chinese/English) multimodal understanding
- you want an Apache-2.0 licensed VLM you can fine-tune or deploy

## When to avoid
- you need a lightweight model for CPU-only or edge devices
- you want a managed API without managing GPU infrastructure
- you need a general-purpose text-only LLM
- you require the newest multimodal models with broader ecosystem support

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, llm-inference, computer-vision, nlp
- domain: large-language-models, computer-vision, artificial-intelligence
- platform: python
- tags: multimodal, vision-language-model, video-understanding, llama3, image-captioning, vqa, video, gpu, linux

## Member repositories
- zai-org/CogVLM2 (main) score 28

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:51.258288+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:31:16.395283+00:00, confidence not recorded.
  - readme: https://github.com/zai-org/CogVLM2 (fetched 2026-08-28T04:06:51.258288+00:00, sha 4f72524c3703)
- Data as of 2026-08-30T08:39:29.467469+00:00.