glm-4.6

completions

byzai

glm-4.6

completions

Published by: z-aiProvider:

zai

GLM-4.6 achieves comprehensive enhancements across multiple domains, including real-world coding, long-context processing, reasoning, searching, writing, and agentic applications.

Released

Sep 30, 2025

Knowledge

Apr 3, 2025

License

MIT

Context

200K

Input

$0.6 / 1M tokens

Output

$2.2 / 1M tokens

Capabilities: tools, reasoning

Accepts: text

Returns: text

Released Sep 30, 2025Knowledge Cutoff: Apr 3, 2025License: MIT

Context: 200K Input: $0.6 / 1M tokensOutput: $2.2 / 1M tokensCapabilities: tools, reasoningAccepts: textReturns: text

Access glm-4.6 through LangDB AI Gateway

Recommended

Integrate with z-ai's glm-4.6 and 250+ other models through a unified API. Monitor usage, control costs, and enhance security.

Unified API

Cost Optimization

Enterprise Security

Get Started Now

Free tier available • No credit card required

Instant Setup

99.9% Uptime

10,000+Monthly Requests

Benchmark Results for glm-4.6

Category Performance Scores:

Academia: Score 62.85 (Top 16% - Rank #54)
Finance: Score 44.50 (Top 44% - Rank #148)
Marketing: Score 47.02 (Top 42% - Rank #141)
Maths: Score 44.30 (Top 49% - Rank #165)
Programming: Score 38.70 (Top 31% - Rank #104)
Science: Score 71.57 (Top 20% - Rank #67)
Writing: Score 48.02 (Top 44% - Rank #148)

Overall Performance: 50.993809523809524 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
AA Coding Index	38.70	Top 31%	Programming
AAII	44.70	Top 24%	General
AA Math Index	44.30	Top 49%	Mathematics
GPQA	81.00	Top 9%	STEM (Physics, Chemistry, Biology)
HLE	5.20	Top 39%	General Knowledge
LiveCodeBench	56.10	Top 31%	Programming
MMLU-Pro	78.40	Top 37%	General Knowledge
SciCode	33.10	Top 38%	Scientific

GPQA Score: 81.00 - Graduate-level reasoning benchmark

Model Comparison:

Provider: zai

Model Type: completions

Context Size: 200000 tokens

Comparing against 335 models in the database

Performance Analytics for glm-4.6

Usage Statistics (Last 2 Days):

Total Requests: 14 API calls
Average TPS: 0.00 tokens per second
Average Response Time: 975.60ms
Average Time to First Token: 975.60ms
Total Cost: $0.00
Average Request Cost: $0.0000

Daily Performance Breakdown:

Date	Requests	TPS	Response Time	TTFT	Cost
10/4/2025	12	0.00	789.80ms	789.80ms	$0.00
10/8/2025	2	0.00	2090.70ms	2090.70ms	$0.00

Performance Summary:

Model: glm-4.6 by zai

Monitoring Period: 10/2/2025 to 10/9/2025

Average Daily Requests: 7

Peak Daily Requests: 12

Statistics

View Full Statistics

Request Volume

Daily API requests

Performance (TPS)

Tokens per second

0.00 tokens/s

Category Scores

Benchmark Tests

View Other Benchmarks

AA Coding Index

38.7

Programming

AAII

44.7

General

AA Math Index

44.3

Mathematics

GPQA

81.0

STEM (Physics, Chemistry, Biology)

HLE

5.2

General Knowledge

LiveCodeBench

56.1

Programming

MMLU-Pro

78.4

General Knowledge

SciCode

33.1

Scientific

Metric	AA Coding Index	AAII	AA Math Index	GPQA	HLE	LiveCodeBench	MMLU-Pro	SciCode
Score	38.7	44.7	44.3	81.0	5.2	56.1	78.4	33.1

Compare with Similar Models

gemini-2.5-pro-preview

Code Examples

Integration samples and API usage

Code Samples for glm-4.6

Python SDK Example:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.us-east-1.langdb.ai/projects/<your_project_id>",
    api_key="<your_api_key>"
)

response = client.chat.completions.create(
    model="glm-4.6",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

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

TypeScript SDK Example:

import OpenAI from 'openai';

const client = new OpenAI({
    baseURL: "https://api.us-east-1.langdb.ai/projects/<your_project_id>",
    apiKey: "<your_api_key>"
});

const response = await client.chat.completions.create({
    model: "glm-4.6",
    messages: [
        { role: "user", content: "Hello, how are you?" }
    ]
});

console.log(response.choices[0].message.content);

cURL Example:

curl -X POST "https://api.us-east-1.langdb.ai/projects/<your_project_id>/v1/chat/completions" \
  -H "Authorization: Bearer <your_api_key>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-4.6",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: glm-4.6

Provider: zai

API Endpoint: $https://api.us-east-1.langdb.ai

Create API Key

Related Models

Similar models from zai

glm-4.6

glm-4.6

Access glm-4.6 through LangDB AI Gateway

Statistics

Category Scores

Benchmark Tests

Compare with Similar Models

Code Examples

Related Models

glm-4-32b

glm-4.5

glm-4.5-air

glm-4.5-airx

glm-4.5v

glm-4.5-x

glm-4.6 by zai - AI Model Details, Pricing, and Performance Metrics

glm-4.6

glm-4.6

Access glm-4.6 through LangDB AI Gateway

Statistics

Category Scores

Benchmark Tests

Compare with Similar Models

Code Examples

Related Models

glm-4-32b

glm-4.5

glm-4.5-air

glm-4.5-airx

glm-4.5v

glm-4.5-x