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GLM 5.2 (batch)

Released at: June 16, 2026

API StatusAvailable for integration
Context Window512,000 tokens✓ verified today
Input Price / MTok$0.70✓ verified today
Output Price / MTok$2.20✓ verified today

Model Overview

Zhipu AI · Active Model

  • Long-Context
  • API Available
  • Vetted Benchmarks
  • Production Ready

GLM 5.2 (batch) by Zhipu AI — Technical Architecture, Empirical Benchmarks & API Specs

1. Executive Summary & Core Positioning§

GLM 5.2 (batch) is an advanced artificial intelligence model engineered by Zhipu AI. Tailored for complex multi-step reasoning, programming synthesis, and extended document comprehension, GLM 5.2 (batch) represents a key architectural iteration in the Zhipu AI model family. First released in 2026-06-16, it serves enterprise developers, research teams, and autonomous system architects requiring strict instruction compliance.

Featuring an input capacity of 512,000 tokens (approximately 683 words), GLM 5.2 (batch) processes multi-file code repositories, lengthy technical reports, and complex prompts in a single inference call.


2. Technical Architecture & Verified Specifications§

Official specification breakdown for GLM 5.2 (batch) based on verified provider metadata:

  • Model Name: GLM 5.2 (batch)
  • Developer / Provider: Zhipu AI
  • Context Window Capacity: 512,000 tokens (~683 words)
  • Modality Support: Text, Code
  • API Availability: Available via API Gateway
  • Tool-Calling Accuracy Score: Pending Empirical Benchmark
  • Time to First Token (TTFT): Varies by Host Provider

3. Benchmark Evaluations & Performance Metrics§

GLM 5.2 (batch) undergoes standardized evaluation across key industry benchmark suites:

  • MMLU (Massive Multitask Language Understanding): Evaluates multi-subject knowledge across STEM, humanities, and social sciences.
  • HumanEval & SWE-bench: Assesses functional Python code synthesis and real-world software engineering bug resolution.
  • GSM8K & MATH: Tests multi-step arithmetic reasoning and formal mathematical proof construction.
  • Chatbot Arena ELO: Evaluates human preference, instruction following, and conversational quality against rival models.

4. Developer API & Integration Specs§

Programmatic integration for GLM 5.2 (batch) follows standard OpenAI-compatible REST endpoints.

import os
import requests

api_key = os.getenv("MODEL_API_KEY")
url = "https://openrouter.ai/api/v1/chat/completions"

headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

payload = {
    "model": "glm-5-2-batch",
    "messages": [
        {"role": "system", "content": "You are a senior software architect and AI system evaluator."},
        {"role": "user", "content": "Analyze system architecture bottlenecks and suggest refactoring strategies."}
    ],
    "temperature": 0.1,
    "max_tokens": 2048
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

5. Production Use Cases & Deployment Scenarios§

5.1 Autonomous Agents & Tool Execution§

Given its instruction compliance and tool-calling capabilities (Pending Empirical Benchmark), GLM 5.2 (batch) is frequently integrated as the reasoning engine for autonomous software agents, browser automation pipelines, and API orchestrators.

5.2 Enterprise Document Synthesis§

With its 512,000 tokens input capacity, engineering and legal teams process full regulatory filings, annual corporate disclosures, and technical documentation directly without context loss.

5.3 Programmatic Code Generation§

Development teams utilize GLM 5.2 (batch) for automated code generation, pull request audits, unit test suite creation, and language migration (e.g. Python to Rust).


6. Token Economics & Pricing Breakdown§

Inference pricing per million tokens for GLM 5.2 (batch):

  • Input Token Cost: $0.70 per MTok
  • Output Token Cost: $2.20 per MTok
  • Prompt Caching Discounts: Supported on selected API providers (up to 50% savings on repeated prompt prefixes)
  • Batch Processing: Available for non-latency-sensitive bulk inference workloads

7. Comparative Specification Matrix§

Metric / Parameter**GLM 5.2 (batch)**Provider Ecosystem Baseline
DeveloperZhipu AIIndustry Average
Context Window512,000 tokens128,000 tokens
Input Price / MTok$0.70Variable
Output Price / MTok$2.20Variable
API AccessSupportedStandard

8. Frequently Asked Questions (FAQ)§

Q: What is GLM 5.2 (batch)'s context window limit?§

A: GLM 5.2 (batch) supports an input context window of 512,000 tokens.

Q: What is the API pricing for GLM 5.2 (batch)?§

A: GLM 5.2 (batch) is priced at $0.70 per million input tokens and $2.20 per million output tokens.

Q: Is GLM 5.2 (batch) accessible via API?§

A: Yes, GLM 5.2 (batch) is available for programmatic integration.

Developer
Zhipu AI✓ verified today
Release Date
June 16, 2026✓ verified today
Context Window
512,000 tokens683 words✓ verified today
API Access
Publicly AvailableIntegrate via official API✓ verified today
Input Cost
$0.70per million tokens✓ verified today
Output Cost
$2.20per million tokens✓ verified today
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Vetted Benchmarks

GPQA(estimated)Score: 39.6% (Top 66%)
HellaSwag(estimated)Score: 81.8% (Top 66%)
HumanEval(estimated)Score: 77.0% (Top 75%)
MATH(estimated)Score: 54.2% (Top 70%)
MMLU(estimated)Score: 78.8% (Top 73%)
MT-Bench(estimated)Score: 8.4 (Top 69%)

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Originally published on llmdb.app

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