# Zhipu AI Releases GLM-4.7-Flash MoE Model

> The new Mixture-of-Experts model from the Beijing-based AI company is optimized for speed and released under the permissive MIT license.

Published by The Open Weights on Jan 19, 2026. Canonical: https://theopenweights.com/news/glm-4-7-flash-x2iw

## Key facts

- Company: Zhipu AI
- Model: GLM-4.7-Flash
- Version: 4.7-Flash
- Category: Text / LLM
- Modalities: Text / LLM
- License: MIT (Open weights, commercial use allowed)
- Active parameters: 3B
- Context window: 203K tokens
- Architecture: Glm4MoeLiteForCausalLM
- Precision: BF16
- Weights size: 62.4 GB
- Significance: notable
- Published: 2026-01-19
- Last verified: 2026-06-17
- Hugging Face: https://huggingface.co/zai-org/GLM-4.7-Flash
- Canonical URL: https://theopenweights.com/news/glm-4-7-flash-x2iw

Chinese AI firm Zhipu AI has released GLM-4.7-Flash, a new language model designed for high-speed inference. It employs a Mixture-of-Experts (MoE) architecture, a technique that allows models to scale up their parameter counts while keeping computational costs manageable during inference.

The 'Flash' in its name signals the model's primary goal: performance. MoE models achieve this by selectively activating only a fraction of their total parameters—the 'experts'—to process any given input. This makes them significantly faster and more efficient for real-time applications compared to dense models of a similar size.

## A Permissive License for Commercial Use

Perhaps most notably for developers and businesses, GLM-4.7-Flash is available under the MIT license. This is one of the most permissive open-source licenses, imposing very few restrictions on reuse and allowing for broad commercial applications. This combination of an efficient architecture and a business-friendly license makes the model an attractive option for integration into products and services.

The model is the latest addition to Zhipu AI's GLM-4 family of models. While specific details on its total parameter count and context length have not been disclosed, developers can access the model weights and resources on its [official Hugging Face repository](https://huggingface.co/zai-org/GLM-4.7-Flash).

## Get the model

- [Hugging Face](https://huggingface.co/zai-org/GLM-4.7-Flash)

## Sources

- [zai-org/GLM-4.7-Flash](https://huggingface.co/zai-org/GLM-4.7-Flash) — Hugging Face, Jan 19, 2026

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Source: The Open Weights (https://theopenweights.com/). Aggregated and written by Claude, curated by humans. Cite as: "Zhipu AI Releases GLM-4.7-Flash MoE Model", The Open Weights, Jan 19, 2026, https://theopenweights.com/news/glm-4-7-flash-x2iw