Moduck

Zhipu AI: GLM-5.2

Open flagship GLM for long-horizon coding agents and million-token context work

Model lab
Zhipu AI
Model family
glm

Model resources

Modalitiestext → text
Context window1,000,000
Maximum output131,072
InputUSD 0.24 / 1M tokens
OutputUSD 0.84 / 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-5.2.

import os
import requests

base_url = "https://api.moduck.ai/v1"
api_key = os.environ["MODUCK_API_KEY"]
model_id = "zhipuai/glm-5.2"

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-5.2 API Pricing

TypePrice information
InputUSD 0.24 / 1M tokens
OutputUSD 0.84 / 1M tokens
Cached inputUSD 0.04 / 1M tokens

Benchmarks

Max

Intelligence Index · v4.333.7
Coding Index68.8
Agentic Index38.4
BenchmarkScoreMeasurementSource
SWE-Bench Pro62.1resolve rate · Date: 2026-06-16
Terminal-Bench82.7success rate · Harness: Claude Code · Version: 2.1 · Date: 2026-06-16
FrontierSWE74.4dominance · Date: 2026-06-16
Humanity's Last Exam40.5accuracy · Dataset: text-only subset · Date: 2026-06-16
Humanity's Last Exam54.7accuracy · Dataset: text-only subset · Variant: with tools · Date: 2026-06-16
CritPt20.9accuracy · Date: 2026-06-16
AIME99.2accuracy · Version: 2026 · Date: 2026-06-16
HMMT94.4accuracy · Version: November 2025 · Date: 2026-06-16
HMMT92.5accuracy · Version: February 2026 · Date: 2026-06-16
IMOAnswerBench91accuracy · Date: 2026-06-16
GPQA Diamond91.2accuracy · Date: 2026-06-16
NL2Repo48.9resolve rate · Date: 2026-06-16
DeepSWE46.2resolve rate · Date: 2026-06-16
Program Bench63.7score · Date: 2026-06-16
Terminal-Bench81success rate · Harness: Terminus 2 · Version: 2.1 · Date: 2026-06-16
PostTrainBench34.3score · Date: 2026-06-16
SWE Marathon13resolve rate · Date: 2026-06-16
MCP Atlas76.8score · Dataset: public subset · Date: 2026-06-16
Tool-Decathlon48.2score · Date: 2026-06-16

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 · Max

Output speed87.65 tokens/s
Time to first token3.81 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
Max87.65 tokens/s3.81 s——

Performance trends

Throughput87.65 tok/sCurrent
Time to first token3.81 sCurrent
End-to-end latency8.0 sCurrent
Throughput
Current87.65 tok/s
Window average90.1 tok/s
Time to first token
Current3.81 s
Window average4.0 s
End-to-end latency
Current8.0 s
Window average7.5 s
Tail latency (P99)
Current17.1 s
Window average16.9 s
Prompt cache hit rate
Current18.2%
Window average24.7%
Error rate
Current2.1%
Window average0.2%

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-5.2 Compare models

ModelInput priceOutput priceContext windowCapabilities
GLM-5.2This pageUSD 0.24 / 1M tokensUSD 0.84 / 1M tokens1,000,000Text 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-5.1USD 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
GLM-5USD 0.76 / 1M tokens · Quantization fp8USD 2.04 / 1M tokens · Quantization fp8204,800Text output · Reasoning · Tool calling

Model specifications

Input
text
Output
text
Context window
1,000,000
Maximum output
131,072
Release date
2026-06-13
Attachments
No
Reasoning
Yes
Tool calling
Yes
Structured output
Yes
Temperature setting
Yes
Open weights
Yes

Frequently asked questions

What is GLM-5.2 for?

Open flagship GLM for long-horizon coding agents and million-token context work

What inputs and outputs does GLM-5.2 support?

Recorded inputs: text; outputs: text.

How is GLM-5.2 priced?

The pricing table shows the current recorded Moduck price. For example: Input USD 0.24 / 1M tokens; Output USD 0.84 / 1M tokens. See the pricing table for all units, variants, and conditions.

What specifications are recorded for GLM-5.2?

Current model records list Context window 1,000,000 tokens; Maximum output 131,072 tokens.

What model parameter does the Quickstart use?

The example uses zhipuai/glm-5.2. 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.