Moduck

Zhipu AI: GLM-4.6

Late GLM-4 workhorse for coding agents, reasoning, and structured tasks

Model lab
Zhipu AI
Model family
glm

Model resources

Modalitiestext → text
Context window204,800
Maximum output131,072
Input · Base context tier (boundary 32000 tokens)USD 0.2191792 / 1M tokens
Output · Base context tier (boundary 32000 tokens)USD 0.8767168 / 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-4.6.

import os
import requests

base_url = "https://api.moduck.ai/v1"
api_key = os.environ["MODUCK_API_KEY"]
model_id = "zhipuai/glm-4.6"

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-4.6 API Pricing

TypePrice information
Input · Base context tier (boundary 32000 tokens)USD 0.2191792 / 1M tokens
Output · Base context tier (boundary 32000 tokens)USD 0.8767168 / 1M tokens
Cached input · Base context tier (boundary 32000 tokens)USD 0.04383584 / 1M tokens

Benchmarks

Non-reasoning

Intelligence Index · v4.314.9
Coding Index—
Agentic Index—
BenchmarkScoreMeasurementSource
Artificial Analysis Coding Index29.5index · Date: 2026-05-22
SciCode38.4percent correct · Date: 2026-05-22
Terminal-Bench Hard25success rate · Date: 2026-05-22
SWE-Bench Pro9.67resolve rate · Dataset: public

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 speed35.33 tokens/s
Time to first token4.52 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-reasoning35.33 tokens/s4.52 s——

Performance trends

Throughput35.33 tok/sCurrent
Time to first token4.52 sCurrent
End-to-end latency7.9 sCurrent
Throughput
Current35.33 tok/s
Window average34.5 tok/s
Time to first token
Current4.52 s
Window average4.9 s
End-to-end latency
Current7.9 s
Window average7.5 s
Tail latency (P99)
Current17.9 s
Window average16.6 s
Prompt cache hit rate
Current26.2%
Window average23.4%
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-4.6 Compare models

ModelInput priceOutput priceContext windowCapabilities
GLM-4.6This pageUSD 0.2191792 / 1M tokens · Base context tier (boundary 32000 tokens)USD 0.8767168 / 1M tokens · Base context tier (boundary 32000 tokens)204,800Text 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
GLM-5-TurboUSD 0.96 / 1M tokensUSD 3.2 / 1M tokens200,000Text output · Reasoning · Tool calling

Model specifications

Input
text
Output
text
Context window
204,800
Maximum output
131,072
Release date
2025-09-30
Attachments
No
Reasoning
Yes
Tool calling
Yes
Temperature setting
Yes
Open weights
Yes

Frequently asked questions

What is GLM-4.6 for?

Late GLM-4 workhorse for coding agents, reasoning, and structured tasks

What inputs and outputs does GLM-4.6 support?

Recorded inputs: text; outputs: text.

How is GLM-4.6 priced?

The pricing table shows the current recorded Moduck price. For example: Input · Base context tier (boundary 32000 tokens) USD 0.2191792 / 1M tokens; Output · Base context tier (boundary 32000 tokens) USD 0.8767168 / 1M tokens. See the pricing table for all units, variants, and conditions.

What specifications are recorded for GLM-4.6?

Current model records list Context window 204,800 tokens; Maximum output 131,072 tokens.

What model parameter does the Quickstart use?

The example uses zhipuai/glm-4.6. 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.