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GLM-5.3-Flash

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GLM-5.3-Flash is Z.ai's first natively multimodal GLM-5 model: a 320B-parameter mixture-of-experts checkpoint with 18B active parameters, hybrid sparse and linear attention, and MIT-licensed weights.

Provider

Z.ai

Model family

Z.ai GLM

Open-weight multimodal MoE LLM

Cost tier

Flash

Status

Current

Release Aug 26, 2026

Why teams choose it

🧠

Z.ai says the model was previously previewed anonymously as ox-alpha on OpenCode and OpenRouter.

📎

Official architecture notes 320B total / 18B active parameters

hybrid sparse plus linear attention, and about 1M-token long context.

⚙️

This Flash SKU is distinct from hosted GLM-5.3: it is natively multimodal and ships MIT weights.

Tradeoffs to know

  • Published coding, agent, and vision scores are vendor-reported and harness-sensitive.
  • Self-hosting a 320B MoE still requires substantial GPU memory, a supported runtime, and quantization choices.
  • List pricing, launch discounts, and Coding Plan quotas change; confirm current Z.ai terms before production use.

Technical specs

Inputs
text, image, video
Outputs
text
Capabilities
coding, agentic workflows, multimodal reasoning, visual coding, computer use, long-context, open-weight serving
License
MIT
Source
https://z.ai/blog/glm-5.3-flash
Deep Swe V1 1
63.4
Aa Intelligence Index
57
Automationbench V1 0 6
48.8

Benchmarks

Terminal Bench 2 1
84.3
Toolathlon Verified
78.4

Z.ai GLM family lineup


Related models

GLM-5.3-Flash FAQ

What is GLM-5.3-Flash?

GLM-5.3-Flash is Z.ai's first natively multimodal GLM-5 model: a 320B-parameter mixture-of-experts checkpoint with 18B active parameters, hybrid sparse and linear attention, and MIT-licensed weights. Z.ai documents API access as glm-5.3-flash, Coding Plan and ZCode availability, and Hugging Face weights for SGLang, vLLM, and TokenSpeed.

When does GLM-5.3-Flash fit best?

Cost-sensitive coding agents

What should teams watch out for with GLM-5.3-Flash?

Published coding, agent, and vision scores are vendor-reported and harness-sensitive.

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