GLM-5.2: How to Run the 753B MoE Model Locally with Unsloth Quantization
GLM-5.2 is a 753-billion-parameter Mixture-of-Experts model that activates only 40 billion parameters per token, making its compute cost comparable to a 40B model while requiring up to 1.51 TB of RAM…
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GLM-5.2: Running Z.ai's 744B-Parameter Open Model Locally with Unsloth Dynamic GGUFs
Run the new GLM-5.2 model by Z.ai on local hardware!
unsloth.ai·18d agoGLM-5.2: Running Z.ai's 744B-Parameter Open Model Locally with Unsloth Dynamic GGUFs
Run the new GLM-5.2 model by Z.ai on local hardware!
unsloth.ai·18d agoUnsloth Releases Dynamic 2.0 GGUFs for Improved LLM Quantization
A big new upgrade to our Dynamic Quants!
unsloth.ai·4mo ago
NVIDIA Releases Quantized GLM-5.2-NVFP4 Language Model on Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
NVIDIA Releases Quantized GLM-5.2-NVFP4 Language Model on Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Colibri: Run 744B-parameter GLM-5.2 MoE model on consumer hardware with 25GB RAM using pure C
Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 - Just
github.com·2d agoColibri: Run 744B-parameter GLM-5.2 MoE model on consumer hardware with 25GB RAM using pure C
Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 - Just
github.com·2d ago
GLM 5.2 - API Pricing & Benchmarks
GLM 5.2 is a large-scale reasoning model from Z.ai. $0.95 per million input tokens, $3 per million output tokens. 1,048,576 token context wi
openrouter.ai·12d agoGLM-5.2: The Open-Source AI Model Beating GPT-5.5 and Chasing Claude Opus 4.8
Z.ai's GLM-5.2 is a 744B parameter open-weight model that beats GPT-5.5 on multiple coding benchmarks at 1/6th the cost. MIT-licensed, 1M co
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