GLM-5.3

Name: GLM-5.3
Author: Z.ai

Z.aiOpen WeightsPending Human Review

GLM-5.3 advances coding, long-horizon engineering, and vulnerability-analysis capabilities through post-training on the GLM-5.2 base model. The model remains text-based and supports a million-token context, selectable reasoning effort, and persistent thinking history. Z.ai initially announced hosted availability before releasing downloadable weights. Those weights use the custom GLM-5.3 License rather than the MIT license of earlier GLM-5 models. It is distinct from GLM-5.3-Flash, which introduces a new native multimodal architecture.

2026-08-14

744B total, 40B activated

Mixture of Experts (MoE) with sparse attention and IndexShare

GLM-5.3 License

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Specifications

Parameters: 744B total, 40B activated
Architecture: Mixture of Experts (MoE) with sparse attention and IndexShare
License: GLM-5.3 License
Context Window: 1,048,576 tokens
Type: text
Modalities: text

Benchmark Scores

Advanced Specifications

Model Family: GLM
API Access: Available
Chat Interface: Not Available

Capabilities & Limitations

Capabilities: reasoningcode generationtool uselong-context understanding
Known Limitations: Self-hosting the full MoE checkpoint requires substantial weight memory.Long-horizon agent results depend on the harness, tools, and reasoning budget.Custom licensing conditions apply to the weights.
Notable Use Cases: software engineering agentscoding assistantsresearch workflows
Function Calling Support: Yes
Tool Use Support: Yes

Resources

Related Models

GLM-5.3-Flash

Z.ai

GLM-5.3-Flash is a natively multimodal GLM model built on a newly trained base. Its hybrid sparse and linear attention, manifold-constrained hyper-connections, and 30T-token multimodal pretraining target strong capability at lower long-context serving cost. Native visual perception supports agents that observe interfaces, inspect rendering results, and refine code. The 320B model activates 18B parameters per token and supports million-token contexts. MIT weights and official API/chat access provide both local and hosted options.

Typemultimodal

Parameters320B total, 18B activated

2026-08-26

Open Weights

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GLM-5.2

Z.ai

GLM-5.2 expands the GLM engineering line to a million-token context and improves reliability on sustained coding tasks. IndexShare reuses sparse-attention indexing across groups of layers to lower long-context computation, while multi-token prediction improvements accelerate decoding. Training emphasizes maintaining goals and using noisy repository and tool context over extended sessions. Public MIT weights and official API access support deployment. The million-token limit is an input-context capability, not a guarantee of reliable retrieval or correct execution at every length. GLM-5.2 Fast is a faster-serving route with the same weights, grouped here rather than cataloged as a separate trained model.

Typetext

Parameters744B total, 40B activated

2026-06-16

Open Weights

Details Compare

GLM-5V-Turbo

Z.ai

GLM-5V-Turbo is Z.ai’s hosted multimodal coding foundation model. It processes text, images, videos, and rendered file content for visual coding, long-horizon planning, and tool-based action execution. Typical workflows include recreating interfaces from screenshots, inspecting rendered pages while debugging, and exploring websites through an agent. Official documentation lists a 200K context and 128K maximum output. A technical report describes the native multimodal model; no public downloadable checkpoint is established for this specific Turbo tier.