# zai-org/VisualGLM-6B

Chinese and English multimodal conversational language model | 多模态中英双语对话语言模型

Repository: https://github.com/zai-org/VisualGLM-6B
Canonical: https://ross.abutalabs.com/products/visualglm-6b
Language: Python
License: Apache-2.0
License Family: permissive
Topics: chatglm-6b, gpt, multi-modal
Last push: 2024-08-23T07:45:06+00:00

## Health v2 (maintenance only)
Score: 30/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 87
- inputs: {"age_days": 1228, "days_push": 740, "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 4154, forks 419 (observed 2026-08-28T04:08:36.534593+00:00)

## What it is
VisualGLM-6B is an open-source multimodal conversational language model supporting images, Chinese, and English, built on ChatGLM-6B with a BLIP2-Qformer visual bridge (7.8B parameters total). It supports quantized deployment on consumer GPUs and offers both Hugging Face and SwissArmyTransformer interfaces.

## Use cases
- chat with a model about an image
- generate image captions in Chinese or English
- run a multimodal LLM locally on a consumer GPU
- fine-tune a vision-language model with LoRA or P-tuning
- build a bilingual image question-answering bot

## When to choose
- you need a bilingual Chinese/English multimodal chat model
- you have limited GPU memory and need INT4 quantized inference
- you want parameter-efficient fine-tuning of a vision-language model

## When to avoid
- you need state-of-the-art multimodal performance (the project recommends CogVLM instead)
- you need an English-only model
- you cannot tolerate hallucinations or factual errors in image descriptions

## Facets
- artifact type: library
- maturity: maintenance
- function: llm-inference, machine-learning, chatbot, image-processing
- domain: large-language-models, artificial-intelligence, computer-vision
- platform: python
- tags: multimodal, vision-language-model, chatglm, blip2, quantization, chinese-english, image-captioning, natural-language-processing, gpu, linux

## Member repositories
- zai-org/VisualGLM-6B (main) score 30

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:36.534593+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 2026-08-29T18:22:53.005845+00:00, confidence not recorded.
  - readme: https://github.com/zai-org/VisualGLM-6B (fetched 2026-08-28T04:08:36.534593+00:00, sha 49f7a5181a50)
- Data as of 2026-08-30T08:39:29.467469+00:00.