Moduck

Zhipu AI: GLM-4.5V

GLM vision model for visual reasoning, documents, and multimodal agents

Model lab
Zhipu AI
Model family
glm

Model resources

Modalitiestext, image, video → text
Context window64,000
Maximum output16,384
Input · Base context tier (boundary 32000 tokens)USD 0.2192 / 1M tokens
Output · Base context tier (boundary 32000 tokens)USD 0.8768 / 1M tokens

Quickstart

Use your Moduck API Key, set the API base URL to https://api.moduck.ai/v1, and set the model parameter to zhipuai/glm-4.5v.

import os
import requests

base_url = "https://api.moduck.ai/v1"
api_key = os.environ["MODUCK_API_KEY"]
model_id = "zhipuai/glm-4.5v"

response = requests.post(
    f"{base_url}/chat/completions",
    headers={
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json",
    },
    json={
        "model": model_id,
        "messages": [{"role": "user", "content": "Hello!"}],
        "stream": False,
    },
    timeout=60,
)
response.raise_for_status()
print(response.json())

Use the familiar OpenAI-style chat request format to make model integration easier.

GLM-4.5V API Pricing

TypePrice information
Input · Base context tier (boundary 32000 tokens)USD 0.2192 / 1M tokens
Output · Base context tier (boundary 32000 tokens)USD 0.8768 / 1M tokens

Benchmarks

Non-reasoning

Intelligence Index · v4.36.7
Coding Index—
Agentic Index—
BenchmarkScoreMeasurementSource
Artificial Analysis Coding Index10.9index · Date: 2026-04-29
SciCode22.1percent correct · Date: 2026-04-29
Terminal-Bench Hard5.3success rate · Date: 2026-04-29

Performance

Measured on the Moduck gateway across live traffic, hour by hour over the last 24 hours. Time to first token is how long before anything appears; throughput is how fast the answer is written after that; end-to-end latency is the whole round trip. Figures are medians unless the card says otherwise.

Artificial Analysis measurement · Non-reasoning

Output speed49.84 tokens/s
Time to first token3.15 s
Time to first answer token—
End-to-end response time—
Measurement variantOutput speedTime to first tokenTime to first answer tokenEnd-to-end response time
Non-reasoning49.84 tokens/s3.15 s——

Performance trends

Throughput49.84 tok/sCurrent
Time to first token3.15 sCurrent
End-to-end latency7.2 sCurrent
Throughput
Current49.84 tok/s
Window average49.6 tok/s
Time to first token
Current3.15 s
Window average3.8 s
End-to-end latency
Current7.2 s
Window average7.5 s
Tail latency (P99)
Current28.8 s
Window average18.1 s
Prompt cache hit rate
Current31.3%
Window average22.5%
Error rate
Current0.0%
Window average0.1%

Availability

Uptime is the share of time at least one provider serving this model responded. Availability is stricter: the share of requests actually served. A provider that answers but fails part of the traffic lowers availability without lowering uptime. Both cover the last three days.

Uptime100%At least one provider responded
Availability100%Requests actually served
Error rate0%Share of failed requests
Served requests, hour by hour
24 hours agoNow

GLM-4.5V Compare models

ModelInput priceOutput priceContext windowCapabilities
GLM-4.5VThis pageUSD 0.2192 / 1M tokens · Base context tier (boundary 32000 tokens)USD 0.8768 / 1M tokens · Base context tier (boundary 32000 tokens)64,000Text output · Reasoning · Tool calling
GLM-4.6VUSD 0.1096 / 1M tokens · Base context tier (boundary 32000 tokens)USD 0.3288 / 1M tokens · Base context tier (boundary 32000 tokens)128,000Text output · Reasoning · Tool calling
GLM-5.3USD 0.0632 / 1M tokens · Quantization fp4USD 1.12 / 1M tokens · Quantization fp41,000,000Text output · Reasoning · Tool calling
GLM-5.2USD 0.24 / 1M tokensUSD 0.84 / 1M tokens1,000,000Text output · Reasoning · Tool calling
GLM-5.1USD 0.36 / 1M tokensUSD 1.72 / 1M tokens200,000Text output · Reasoning · Tool calling

Model specifications

Input
text, image, video
Output
text
Context window
64,000
Maximum output
16,384
Release date
2025-08-11
Attachments
Yes
Reasoning
Yes
Tool calling
Yes
Temperature setting
Yes
Open weights
Yes

Frequently asked questions

What is GLM-4.5V for?

GLM vision model for visual reasoning, documents, and multimodal agents

What inputs and outputs does GLM-4.5V support?

Recorded inputs: text, images, video; outputs: text.

How is GLM-4.5V priced?

The pricing table shows the current recorded Moduck price. For example: Input · Base context tier (boundary 32000 tokens) USD 0.2192 / 1M tokens; Output · Base context tier (boundary 32000 tokens) USD 0.8768 / 1M tokens. See the pricing table for all units, variants, and conditions.

What specifications are recorded for GLM-4.5V?

Current model records list Context window 64,000 tokens; Maximum output 16,384 tokens.

What model parameter does the Quickstart use?

The example uses zhipuai/glm-4.5v. This value comes from the page identifier and is not confirmed as a callable Moduck public ID.

Can I call this model through the Moduck API now?

This page has no verified Moduck API call for this model. A Quickstart example or reserved ID does not establish access; check the models available to your account.