Z.AI: GLM 4 32B

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GLM-4-32B is a 32-billion parameter bilingual (Chinese-English) foundation model by Zhipu AI, pre-trained on 15TB of reasoning-focused data. It delivers performance comparable to GPT-4o on code generation, function calling, and Q&A tasks while remaining deployable on accessible hardware.

Context Window 128K

tokens

Max Output 32K

tokens

Input Cost $0.1

per million tokens

Output Cost $0.1

per million tokens

Release Date Jul 24, 2025

Code Example

Add AI to your app with the Puter.js AI API, no API keys or setup required.

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

puter.ai.chat("Explain quantum computing in simple terms").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").then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

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GLM 5.3 Prime is a high-speed serving tier built on Z.ai's GLM-5.3, offered through third-party inference platforms rather than as an official Z.ai product listing. It runs the same 744-billion-parameter Mixture-of-Experts weights (40 billion active) as standard GLM-5.3, on infrastructure tuned for higher throughput. Vendor reports put its output throughput at 1.5 to 2 times the standard GLM-5.3 endpoint, at roughly double the per-token price, a pattern also seen with GLM-5.2's own "Fast" tier. No independent benchmark of the Prime endpoint exists, but since the weights are unchanged, it should inherit GLM-5.3's reported gains over GLM-5.2, including a 50% jump on Z.ai's Code Bench and gains on Terminal-Bench 3.0 and DeepSWE v1.1. It supports a 1,000,000-token context window, 128,000 max output tokens, three reasoning-effort levels, and function calling. Best suited for agent loops and coding assistants that chain many model calls and are latency-sensitive, where the throughput gain offsets cost.

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GLM 5.3 FlashX

GLM 5.3 FlashX is Z.ai's high-speed serving tier for GLM-5.3-Flash, using the same 320-billion-parameter Mixture-of-Experts weights (18 billion active) rather than a separate model. Z.ai runs it on faster inference infrastructure, reporting speeds up to 200 tokens per second. Because the weights are unchanged, it inherits GLM-5.3-Flash's benchmark results, including 63.4 on DeepSWE v1.1 and 48.8 on AutomationBench, both ahead of GLM-5.2. It keeps the same 1,000,000-token context window, 128,000-token max output, and function calling support. Pricing is $0.37 per million input tokens and $1.25 per million output tokens, about 2.5 times GLM-5.3-Flash's rate. It fits agent loops and coding assistants that call the model repeatedly and need lower per-call latency, where the added throughput offsets the higher per-token price.

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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.

Frequently Asked Questions

How do I use GLM 4 32B?

GLM 4 32B is no longer available through Puter.js. Explore other AI models for alternatives.

What is the pricing for GLM 4 32B?

GLM 4 32B costs $0.1 per 1M input tokens and $0.1 per 1M output tokens.

	Price per 1M tokens
Input	$0.1
Output	$0.1

Who created GLM 4 32B?

GLM 4 32B was created by Z.AI and released on Jul 24, 2025.

What is the context window of GLM 4 32B?

GLM 4 32B supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.

What is the max output length of GLM 4 32B?

GLM 4 32B can generate up to 32K tokens in a single response.

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

Yes — the GLM 4 32B 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.

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