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Z.AI

Z.AI: GLM 5.2 Fast Preview

zhipu/glm-5.2-fast-preview

Access GLM 5.2 Fast Preview from Z.AI using Puter.js AI API.

Get Started
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms", {
    model: "zhipu/glm-5.2-fast-preview"
}).then(response => {
    document.body.innerHTML = response.message.content;
});
<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms", {
            model: "zhipu/glm-5.2-fast-preview"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>
# pip install openai
from openai import OpenAI

client = OpenAI(
    base_url="https://api.puter.com/puterai/openai/v1/",
    api_key="YOUR_PUTER_AUTH_TOKEN",
)

response = client.chat.completions.create(
    model="zhipu/glm-5.2-fast-preview",
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms"}
    ],
)

print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
  -d '{
    "model": "zhipu/glm-5.2-fast-preview",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Model Card

GLM 5.2 Fast Preview is a preview release of Z.ai's high-speed serving tier for GLM-5.2, aimed at cutting response latency and raising throughput over the standard endpoint.

It offers a 1,000,000-token context window and a 131,072-token maximum output, with tool calling, streaming, and context caching. Third-party providers report capabilities on par with standard GLM-5.2 and roughly 1.5 to 2 times its output throughput.

The underlying GLM-5.2 is Z.ai's 744-billion-parameter Mixture-of-Experts model (40 billion active), which scored 62.1 on SWE-bench Pro, ahead of GPT-5.5's 58.6, and ranks as a top open-weight model on long-horizon coding benchmarks.

Pricing is $2.80 per million input tokens and $8.80 per million output tokens. Best suited for latency-sensitive workloads such as real-time chat, multi-turn agent loops, and streaming code generation.

Context Window 1M

tokens

Max Output 131K

tokens

Input Cost $2.8

per million tokens

Output Cost $8.8

per million tokens

Input text

modalities

Tool Use Yes

 

Release Date N/A

 

Model Playground

Try GLM 5.2 Fast Preview instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat zhipu/glm-5.2-fast-preview
Z.AI
Chat with GLM 5.2 Fast Preview
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More AI Models From Z.AI

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GLM 5.3 Flash

GLM 5.3 Flash is a mixture-of-experts model from Z.ai (Zhipu AI), the first natively multimodal release in the GLM-5 family, accepting text and image input. It has 320 billion total parameters with 18 billion active per token, and a hybrid sparse-and-linear attention architecture that Z.ai says cuts attention compute about 3x and KV cache size about 4.4x compared with GLM-5.3. Through this API it offers a 1,000,000 token context window and up to 131,100 output tokens, priced at $0.08 per million input tokens and $0.25 per million output tokens. It supports function calling, and thinking is always on and cannot be disabled. GLM 5.3 Flash beats GLM-5.2 on Z.ai's reported benchmarks (DeepSWE v1.1, 63.4 vs 46.2; AutomationBench, 48.8 vs 26.2) and approaches Claude Opus 4.8 on coding and agentic tasks. Model weights are released under the MIT license.

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GLM 5.3

GLM 5.3 is Z.ai's latest open-weight foundation model, a post-training refresh of GLM-5.2 released August 14, 2026. It keeps the same 744B-parameter Mixture-of-Experts architecture (40B active) and 1M-token context window; all reported gains come from expanded reinforcement-learning post-training rather than a new base model. On Z.ai's internal Code Bench, GLM 5.3 scores 50% higher than GLM-5.2. It also improves on Terminal-Bench 3.0 (4.6 to 28.3) and DeepSWE v1.1 (46.2 to 66.9). Cybersecurity ability grew alongside coding: CyberGym rose from 77.2% to 84.5%, and ExploitBench more than doubled, from 24.4% to 54.4%. The model supports three reasoning-effort levels (low, high, max) via the API, and thinking can no longer be disabled. It is best suited to long-horizon coding agents, repository-scale engineering tasks, and vulnerability research.

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GLM 5.2 Fast

GLM 5.2 Fast is the high-speed serving tier of Z.ai's GLM-5.2, running the same model weights on inference infrastructure tuned for higher throughput. Output quality matches the standard GLM-5.2 endpoint; serving speed and price are the differences. It keeps the full 1M-token context window and 128K max output, along with tool calling, structured output, streaming, optional thinking mode with adjustable reasoning effort, and implicit prompt caching. Providers report roughly 2x the throughput of their standard GLM-5.2 endpoints, with peaks measured at 446 tokens per second. Because the weights are identical, it inherits GLM-5.2's coding results, including 62.1 on SWE-bench Pro. The tradeoff is a higher per-token price than standard GLM-5.2. A fit for agent loops that chain many model calls, real-time coding assistants, and other latency-sensitive workloads.

Frequently Asked Questions

How do I use GLM 5.2 Fast Preview?

You can access GLM 5.2 Fast Preview by Z.AI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.

Is GLM 5.2 Fast Preview free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add GLM 5.2 Fast Preview to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.

What is the pricing for GLM 5.2 Fast Preview?
GLM 5.2 Fast Preview costs $2.8 per 1M input tokens and $8.8 per 1M output tokens.
Price per 1M tokens
Input$2.8
Output$8.8
What is the context window of GLM 5.2 Fast Preview?

GLM 5.2 Fast Preview supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,000 pages of text.

What is the max output length of GLM 5.2 Fast Preview?

GLM 5.2 Fast Preview can generate up to 131K tokens in a single response.

What types of input can GLM 5.2 Fast Preview process?

GLM 5.2 Fast Preview accepts the following input types: text. It produces: text.

Does GLM 5.2 Fast Preview support tool use (function calling)?

Yes, GLM 5.2 Fast Preview supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the GLM 5.2 Fast Preview API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

Get started with Puter.js

Add GLM 5.2 Fast Preview to your app without worrying about API keys or setup.

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