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Zhipu AI

GLM 5.1

Next-generation multilingual language model with state-of-the-art Chinese NLP, 128K context window, and advanced cross-language code generation — built for global developers.

Model Overview

GLM 5.1 by Zhipu AI pushes the boundaries of multilingual understanding, delivering exceptional performance across 40+ languages with a focus on Chinese NLP and code generation.

128K
Context Window (tokens)
40+
Supported Languages
2026
Training Cutoff

Performance Benchmarks

Industry-standard benchmarks demonstrate GLM 5.1's strengths in multilingual tasks, mathematics, and code generation.

CMMLU
96.2%
MultilingualBench
94.1%
CodeGen-Multi
88.7%
HumanEval
87.9%
MATH
85.4%

Key Capabilities

GLM 5.1 is purpose-built for multilingual workflows, from cross-language code to enterprise API development.

Multilingual Code Generation

Generate production-quality code in Python, JavaScript, TypeScript, Go, Rust, Java, and more — with native-level understanding of Chinese documentation and variable naming conventions.

Cross-Language Translation

Seamlessly translate between 40+ languages with exceptional accuracy for CJK (Chinese, Japanese, Korean) languages, technical content, and domain-specific terminology.

Deep Context Understanding

Leverage the 128K token context window for entire codebases, long documents, and complex multi-turn conversations without losing coherence or relevant detail.

API & Backend Development

Design, scaffold, and implement RESTful APIs, GraphQL schemas, database models, and microservice architectures with best-practice patterns and comprehensive error handling.

Quick Start

Use GLM 5.1 through the RusorAgent API with just a few lines of Python.

glm_example.py
import requests

# RusorAgent API endpoint
API_URL = "https://api.rusoragentai.com/v1/chat/completions"
API_KEY = "your-api-key-here"

payload = {
    "model": "glm-5.1",
    "messages": [
        {"role": "system", "content": "You are a helpful multilingual assistant."},
        {"role": "user", "content": "用Python写一个REST API,包含用户认证功能"}
    ],
    "max_tokens": 4096,
    "temperature": 0.7
}

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

response = requests.post(API_URL, json=payload, headers=headers)
result = response.json()

print(result["choices"][0]["message"]["content"])

Ready to Build with GLM 5.1?

Access GLM 5.1 alongside Claude Opus 4.6, GPT-5, and Gemini 2.5 Pro — all from a single API.

View Pricing & Get Started

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