// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "z-ai/glm-4.5x"
}).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: "z-ai/glm-4.5x"
}).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="z-ai/glm-4.5x",
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": "z-ai/glm-4.5x",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
GLM-4.5X is the high-speed serving of GLM-4.5, the flagship agentic model from Z.ai (Zhipu AI). It keeps the same 128K-token context window and 96K maximum output as the standard endpoint but is served for low latency, with generation speed exceeding 100 tokens per second in real-world tests.
The underlying GLM-4.5 ranks near the top globally on an aggregate of 12 benchmark suites (including MMLU Pro, AIME24, MATH 500, and GPQA) and is optimized for tool invocation, web browsing, software engineering, and front-end development. It supports function calling and both thinking and non-thinking response modes.
Choose it over standard GLM-4.5 when latency matters more than cost, for interactive coding assistants, real-time agent loops, and high-concurrency chat. Pricing is $2.20 per million input tokens and $8.90 per million output, roughly four times the standard GLM-4.5 rate.
Context Window 128K
tokens
Max Output 96K
tokens
Input Cost $2.2
per million tokens
Output Cost $8.9
per million tokens
Input text
modalities
Tool Use Yes
Release Date Jul 28, 2025
Model Playground
Try GLM 4.5X instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Z.AI
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.
ChatGLM 5.2
GLM 5.2 is Z.ai's sixth-generation open-weight foundation model, built around a 1M-token context window that can hold entire mid-sized codebases in a single prompt. It uses a 744B-parameter Mixture-of-Experts architecture with an "IndexShare" attention optimization that cuts per-token FLOPs by 2.9x at 1M context, keeping long-context inference practical. A new MTP speculative decoding layer raises acceptance length by up to 20%, reducing latency. Dual reasoning modes (High/Max) let you trade speed for depth on complex tasks. GLM 5.2 scored 62.1 on SWE-bench Pro, outperforming GPT-5.5 (58.6) and its predecessor GLM-5.1 (58.4). It is the top-ranked open-weight model on long-horizon coding benchmarks. Best suited for repository-scale refactoring, multi-step agentic coding, full-codebase analysis, and any workflow that previously required chunking large inputs.
ChatGLM 5.1
GLM-5.1 is a frontier-class reasoning model from Z.ai (formerly Zhipu AI), built as a post-training refinement of GLM-5 with a focus on coding and agentic tasks. It uses a 744B-parameter Mixture-of-Experts architecture with 40B active parameters per token and supports a 200K context window. GLM-5.1 scored 58.4 on SWE-Bench Pro, surpassing GPT-5.4 (57.7) and Claude Opus 4.6 (57.3), and reached 95.3 on AIME 2026. It excels at long-horizon agentic workflows, multi-step tool use, and complex software engineering tasks. The model is text-only — no image or audio input.
Frequently Asked Questions
You can access GLM 4.5X 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.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add GLM 4.5X to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $2.2 |
| Output | $8.9 |
GLM 4.5X was created by Z.AI and released on Jul 28, 2025.
GLM 4.5X supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.
GLM 4.5X can generate up to 96K tokens in a single response.
GLM 4.5X accepts the following input types: text. It produces: text.
Yes, GLM 4.5X supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the GLM 4.5X 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 4.5X to your app without worrying about API keys or setup.
Read the Docs View Tutorials