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  1. Models
  2. Text
  3. Z.AI

GLM 4.5V Thinking

Thinking-enabled GLM 4.5V that surfaces structured reasoning before its final answer. Great for image-grounded analysis, OCR, charts, and deliberate step-by-step responses.

  • Reasoning
  • Vision

Added Nov 22, 2025

Model weights

Pricing

Auto routing · per 1M tokens
Input
$0.60
Output
$1.80
Cache read
$0.30
Compare provider prices

Specifications

Context window
64K
Max output
96K
Parameters
106B / 12B
Total / active

Benchmarks

No public benchmark scores for this model yet.

Providers

Auto routing is available for this model. Explicit provider selection is not available.

Auto
Auto
Recommended
$0.60$1.80$0.30N/AN/A
Batch API
ProviderInputOutputCached input
Auto
Autoz-ai/glm-4.5v:thinking
$0.60/M$1.80/M$0.30/M

Batch rows for this model use normal routing and cost the same as standard API requests. Set provider in a row to choose a provider.

Reliability

Related text models

Compare GLM 4.5V Thinking with similar models from the same provider or model family.

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Apex Flash 1

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Apex Flash 1 is Cantina Security and Yeta's cybersecurity-focused post-train of GLM 5.3 Flash for code investigation and tool use.

Apex Flash 1 Abliterated

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Apex Flash 1 Abliterated is an experimental derivative of Cantina Security and Yeta's Apex Flash 1 with modified refusal behavior.

GLM 5.3 Uncensored

z-ai/glm-5.3-uncensored

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GLM 5.3 Flash Cybersecurity

z-ai/glm-5.3-flash-cybersecurity

GLM 5.3 Flash Cybersecurity is a cybersecurity-focused variant based on the uncensored model, with provider moderation for illegal activities. It supports always-on reasoning, image understanding, tool calling, and a 1,048,576-token context window.

GLM 5.3 Flash

z-ai/glm-5.3-flash

ox-alpha out of stealth! GLM-5.3 Flash is Z.ai's first natively multimodal GLM-5 model, with 320B total parameters and just 18B active parameters for efficient coding, agentic work, and precise 1M-token context. Its hybrid sparse-and-linear attention architecture helps it outperform GLM-5.2 at one-tenth the price while approaching Claude Opus 4.8 on coding and agentic benchmarks.