Atlas / Models / Z Ai / Z.ai: GLM 5.2 (batch)

Z.ai: GLM 5.2 (batch)✓ Catalog verified

z-ai/glm-5.2:batch

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...

Input price
$0.70 /1M
Output price
$2.20 /1M
Context
512K
Modalities
text
Released
Jun 16, 2026
Tool calling
✓ Yes
Atlas signal
88/100
01

Overview

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...

Access: available through the official Z Ai API. Context window: 512K.

Pricing and metadata from the ModelsAtlas catalog.Last refreshed Aug 9, 2026
02

Specifications

API identifierz-ai/glm-5.2:batch
ProviderZ Ai
Model typeText LLM
Context window512K catalog
Input modalitiestext
Output modalitiestext
ReleasedJun 16, 2026
ModeratedNo
Architecture modalitytext->text
Supported parameters
frequency_penaltyinclude_reasoninglogit_biasmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatstopstructured_outputstemperaturetool_choicetoolstop_ktop_p
Source: provider documentation + catalog feedMethodology →

API defaults

Default parameters
{
  "top_k": null,
  "top_p": 0.95,
  "temperature": 1,
  "presence_penalty": null,
  "frequency_penalty": null,
  "repetition_penalty": null
}
03

Pricing

Live pricing components for z-ai/glm-5.2:batch as published in the catalog.

$0.70
Input /1M
$2.20
Output /1M
Per request
Per image
Pricing componentRaw unit priceNormalizedUnit
Prompt tokens$7e-7$0.70 / 1MPer input token
Completion tokens$0.0000022$2.20 / 1MPer output token
Request feeN/AN/APer request
Image feeN/AN/APer image unit
Web search feeN/AN/APer search request
Source: catalog pricing feedCompare all pricing →Cheapest models →
04

Cost calculator

Estimate monthly spend from your own token volumes.

Scale / Volume

Estimated Total Cost

$0.79Calculated from current list pricing in the ModelsAtlas catalog.
05

Capabilities

CapabilityStatusWhat it means
Visual UnderstandingNot advertisedImage and document analysis support
Audio ProcessingNot advertisedSpeech and voice aligned flows
Tool Calling✓ SupportedSupports tools / function calling
Self-HostingNot advertisedDeploy outside managed APIs
Derived from catalog capability tags and supported parameters
06

Capability signals

Directional signals derived from model metadata and capability tags — not official benchmark submissions.

Z.ai: GLM 5.2 (batch)
MMLU Signal (Reasoning)
97signal
Coding Signal (HumanEval proxy)
88signal
Math Signal (GSM8K proxy)
83signal
Science Signal (GPQA proxy)
83signal
Estimated from metadata — not an official benchmark runAll benchmarks →Methodology →
07

Quick start

Call Z.ai: GLM 5.2 (batch) through an OpenAI-compatible client.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="z-ai/glm-5.2:batch",
    messages=[{"role": "user", "content": "Explain quantum physics."}]
)

print(response.choices[0].message.content)
08

Alternatives

Closest models by context window from a different provider.

09

Sources & attribution

Pricing and metadata are maintained in the ModelsAtlas catalog.

Capability bars use metadata tags — directional estimates onlyHow we source and verify data →
10

Frequently asked questions

How much does Z.ai: GLM 5.2 (batch) cost?

$0.70 per 1M input tokens and $2.20 per 1M output tokens on the official Z Ai API.

What is the context window of Z.ai: GLM 5.2 (batch)?

Z.ai: GLM 5.2 (batch) supports up to 512K tokens of context.

Does Z.ai: GLM 5.2 (batch) support tool / function calling?

Yes, Z.ai: GLM 5.2 (batch) supports tool / function calling — you can register tools and the model will emit structured tool calls.

How do I access Z.ai: GLM 5.2 (batch)?

Use the official Z Ai API with the model id `z-ai/glm-5.2:batch`. See the Quick start section above for code examples.