GLM 4 Plus

Zhipu GLM-4-Plus is a large-scale pre-trained language model launched by Zhipu AI. It is an advanced version in the GLM-4 series, designed specifically for complex tasks and high-quality interactions, with stronger reasoning ability and a broader knowledge coverage area.

Intelligence(Strong)

Speed(Slow)

Input Supported Modalities

Yes

Is Reasoning Model

128,000

Context Window

4,096

Maximum Output Tokens

2024-01-31

Knowledge Cutoff

Pricing

￥4.5 /M tokens

Input

￥22.5 /M tokens

Output

￥9 /M tokens

Blended Price

Quick Simple Comparison

GLM-4-Air-250414

￥0.07

GLM-4-Plus

￥0.63

Basic Parameters

GPT-4.1 Technical Parameters

Parameter Count

Not Announced

Context Length

128.00k tokens

Training Data Cutoff

2024-01-31

Open Source Category

Proprietary

Multimodal Support

Text, Image

Throughput

Release Date

2024-06-09

Response Speed

45.3 tokens/s

Benchmark Scores

Below is the performance of claude-monet in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.

Intelligence Index

Large Language Model Intelligence Level

8520

Large Language Model Intelligence Level

Coding Index

Indicator of AI model performance on coding tasks

8410

Indicator of AI model performance on coding tasks

Math Index

Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks

MMLU Pro

Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video

78.6

Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video

GPQA

Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions

68.4

Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions

HLE

The model's comprehensive average score on the Hugging Face Open LLM Leaderboard

83.1

The model's comprehensive average score on the Hugging Face Open LLM Leaderboard

LiveCodeBench

Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems

79.2

Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems

SciCode

The model's capability in code generation for scientific computing or specific scientific domains

72.1

The model's capability in code generation for scientific computing or specific scientific domains

HumanEval

Score achieved by the AI model on the specific HumanEval benchmark test set

81.5

Score achieved by the AI model on the specific HumanEval benchmark test set

Math 500 Score

Score on the first 500 larger, more well-known mathematical benchmark tests

70.2

Score on the first 500 larger, more well-known mathematical benchmark tests

AIME Score

An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)

65.3

An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)

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