# GLM-5.2 Benchmarks Highlight LLM Performance

> Published 2026-06-17 · https://www.promptzone.com/arlo_mensah/glm-52-benchmarks-highlight-llm-performance-54e9

GLM-5.2 surfaced in benchmarks tracked by Artificial Analysis and flagged on [Hacker News](https://artificialanalysis.ai/models/glm-5-2) with 35 points and 5 comments. The model posts strong results in quality index while maintaining competitive pricing and latency.

> **Model:** GLM-5.2 | **Quality Index:** 68 | **Speed:** 38 tokens/s
> **Price:** $0.35 / M tokens | **Context:** 128K | **License:** Commercial

## What It Is

GLM-5.2 is a large language model from Zhipu AI evaluated on the Artificial Analysis platform. It supports long context windows and delivers balanced output across reasoning, coding, and multilingual tasks.


![GLM-5.2 Benchmarks Highlight LLM Performance](https://blogs.nvidia.com/wp-content/uploads/2025/04/water-efficiency-hero-resized.jpg)

## Benchmarks and Key Numbers

The model records a quality index of 68, placing it near several frontier-class systems. Output speed reaches 38 tokens per second with 128K context support.

| Metric              | GLM-5.2 | GPT-4o     | Claude 3.5 Sonnet |
|---------------------|---------|------------|-------------------|
| Quality Index       | 68      | 71         | 70                |
| Speed (tokens/s)    | 38      | 85         | 42                |
| Price ($/M tokens)  | 0.35    | 2.50       | 3.00              |
| Context Window      | 128K    | 128K       | 200K              |

Early HN comments noted the favorable price-to-performance ratio compared with higher-cost closed models.

## How to Try It

Access GLM-5.2 through the Artificial Analysis playground or Zhipu AI API endpoints. Developers can run standardized prompts directly on the benchmark site to replicate reported scores.

{% details "API example" %}
Use the Zhipu AI Python SDK with your API key and specify model name `glm-5.2` for inference calls.
{% enddetails %}

## Pros and Cons

- Strong quality index at low per-token cost
- Solid 38 tokens/s inference speed on standard hardware
- 128K context window suitable for document tasks
- Limited public fine-tuning options compared with open-weight models
- Fewer third-party integrations than OpenAI or Anthropic offerings

## Alternatives and Comparisons

Direct competitors include GPT-4o and Claude 3.5 Sonnet. GLM-5.2 undercuts both on price while delivering within 5% of their quality index scores.

## Who Should Use This

Teams running high-volume inference on a budget benefit most. Skip GLM-5.2 if maximum speed or extensive plugin ecosystems are required.

> **Bottom line:** GLM-5.2 delivers near-frontier quality at roughly one-seventh the price of leading alternatives.

Developers tracking cost-efficient models should add GLM-5.2 to their evaluation shortlist for production workloads.