GLM-4 Plus: Complete Benchmark Performance Guide

other glm-4-plus 2024-08-12 Proprietary

In-depth analysis of GLM-4 Plus performance on MMLU, HumanEval, GSM8K, MATH, BBH benchmarks, including pricing and use cases.

Key Specifications

Vendorother
Versionglm-4-plus
Release Date2024-08-12
Context Window131072 tokens
Input Modalitiestext, image
Output Modalitiestext
LicenseProprietary
Documentationhttps://huggingface.co/models

Benchmark Performance

Benchmark Score Unit Evaluated At Notes Source
MMLU 84.3 % 2024-08-12 5-shot view
HUMANEVAL 72.7 pass@1 2024-08-12 — view
GSM8K 81.8 % 2024-08-12 0-shot CoT view
MATH 53.3 % 2024-08-12 0-shot CoT view
BBH 83.6 % 2024-08-12 3-shot CoT view
GPQA 35.4 % 2024-08-12 0-shot view
IFEVAL 79.2 % 2024-08-12 prompt_strict view
ARC 94.5 % 2024-08-12 challenge view
MUSR 51.3 % 2024-08-12 0-shot view
WINOGRANDE 85.8 % 2024-08-12 0-shot view

Pricing

Tier Price Currency
Input$0.5 / MtokUSD
Output$0.5 / MtokUSD
Cache Read$0 / MtokUSD
Cache Write$0 / MtokUSD

Source: https://huggingface.co/models · as of 2024-08-12

Compliance

  • Data Residency: self-host
  • SOC2: ✗
  • HIPAA: ✗
  • GDPR: ✗
  • ISO 27001: ✗

GLM-4 Plus

Model Overview

清华智谱 GLM-4 Plus 旗舰模型, 131K 上下文, 支持文本与图像输入, 中文能力突出。

Core Specifications

Vendor Version Release Date Context Window Input Modalities Output Modalities License
Other glm-4-plus 2024-08-12 131K text, image text Proprietary

Benchmark Performance

Benchmark Score Unit Notes
MMLU (Massive Multitask Language Understanding) 84.3 % 5-shot
HumanEval 72.7 pass@1 —
GSM8K (Grade School Math 8K) 81.8 % 0-shot CoT
MATH 53.3 % 0-shot CoT
BBH (BIG-Bench Hard) 83.6 % 3-shot CoT
GPQA 35.4 % 0-shot
IFEval 79.2 % prompt_strict
ARC 94.5 % challenge
MUSR 51.3 % 0-shot
WinoGrande 85.8 % 0-shot

Pricing

Input Output Cache Read Cache Write
— — — —

per million tokens

Strengths

  • MMLU score 84.3, strong knowledge reasoning.
  • Input Modalities: text, image, audio.

Weaknesses

  • Proprietary, not self-hostable.

Use Cases

  • Code generation and debugging
  • Vision and image understanding
  • Agent workflows and tool use

References