zai-org/GLM-130B

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7651 stars · 599 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

GLM-130B is an open bilingual (English and Chinese) 130-billion-parameter dense language model pre-trained with the General Language Model (GLM) algorithm, released with code and checkpoints for reproducible evaluation. It supports inference on a single A100 or V100 server, with INT4 quantization reducing requirements to 4x RTX 3090 GPUs.

Use cases

• run inference with a 130B bilingual English-Chinese language model
• reproduce benchmark results for large language models on 30+ tasks
• quantize a large model to INT4 to fit on consumer GPUs
• evaluate zero-shot performance on Chinese CLUE and FewCLUE benchmarks
• compare against GPT-3, OPT, and BLOOM on LAMBADA and MMLU

When to choose

• you need an open bilingual Chinese-English large model with downloadable checkpoints
• you want reproducible evaluation of a 130B model on limited hardware via INT4 quantization
• you need strong zero-shot Chinese language understanding performance

When to avoid

• you need a modern chat model with long context - use ChatGLM2-6B or newer instead
• you only need English-only models or smaller deployable models
• you lack multi-GPU server hardware and cannot use quantization

Facets

library · maturity maintenance

llm-inference llm-training machine-learning nlp large-language-models artificial-intelligence deep-learning python bilingual chinese-english glm pretrained-model quantization int4 iclr-2023 model-checkpoints natural-language-processing linux gpu docker

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