BytePlus: GLM-5.2
byteplus/glm-5-2-260617
Access GLM-5.2 from BytePlus 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: "byteplus/glm-5-2-260617"
}).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: "byteplus/glm-5-2-260617"
}).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="byteplus/glm-5-2-260617",
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": "byteplus/glm-5-2-260617",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
GLM-5.2 is an open-weight Mixture-of-Experts model from Zhipu AI (Z.ai), available here through BytePlus's hosted API.
The model has roughly 744 billion total parameters and a 1 million token context window, and Z.ai released its weights under an MIT license.
GLM-5.2 is built for coding, particularly long-horizon and agentic coding tasks. On SWE-bench Pro it scored 62.1, ahead of GPT-5.5 (58.6) and its predecessor GLM-5.1 (58.4). On the Artificial Analysis Intelligence Index it scored 51, the highest score among open-weight models at release.
It suits teams building coding agents or working with large codebases who want an open-weight model, accessed here through BytePlus's API instead of self-hosting.
Context Window 1M
tokens
Max Output 128K
tokens
Input Cost $1.4
per million tokens
Output Cost $4.4
per million tokens
Input text
modalities
Tool Use Yes
Release Date Jun 17, 2026
Model Playground
Try GLM-5.2 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From BytePlus
Dola Seed 2.1 Turbo
Dola Seed 2.1 Turbo is ByteDance's faster, lower-cost variant in the Seed 2.1 family, offered internationally through BytePlus's Model Ark platform. It accepts text, image, and video input, with a 256K context window and function calling for agent workflows. On ByteDance's own benchmarks against Claude Opus 4.7, GPT-5.5, and Gemini 3.1 Pro, Turbo scores 89 on VideoMME for long video understanding and 79.2 on OVOBench for streaming video, ahead of Gemini 3.1 Pro's 86.7 and 64.1. It scores 88.0 on BeyondAIME reasoning, above Seed 2.1 Pro's 87.0. On knowledge tests like SuperGPQA it trails GPT-5.5 and Gemini. These are vendor-reported figures, not independently verified. It suits high-volume API use such as video analysis, document processing, and agent pipelines, where cost and video handling matter more than peak coding scores.
ImageDola Seedream 5.0 Pro
Dola Seedream 5.0 Pro is ByteDance's Seedream 5.0 Pro image generation and editing model, offered here through BytePlus's ModelArk API under the "Dola" branding BytePlus uses across its hosted model lineup. It generates images as independently editable layers, separating subjects, text, and background so pieces can be repositioned or swapped after generation. It supports pixel-level editing through selection points, arrows, and annotation boxes, reads color codes and material specifications, and renders text across 14 or more languages including Arabic, Korean, Thai, French, Russian, and Japanese. On Artificial Analysis's independent Text-to-Image Elo leaderboard it scores 1,283, ranking 8th overall, ahead of Black Forest Labs' FLUX.2 Max (1,233) and just behind Google's Nano Banana Pro (1,299). It fits production teams that need layered, editable output and multilingual text rather than a single flattened image.
VideoDreamina Seedance 2.0 Mini
Dreamina Seedance 2.0 Mini is the smallest, most economical tier of ByteDance's Seedance 2.0 video family, distributed under the Dreamina brand and hosted here via BytePlus. BytePlus positions it as roughly twice as fast as the Fast tier and about half the list price of the full Seedance 2.0 model, while still accepting image, video, and audio references alongside a text prompt. Output is capped at 720p and 480p with clips up to 15 seconds at 24fps, the same resolution ceiling as the Fast tier. ByteDance markets it for everyday production work such as brainstorming, quick mockups, and short-form video, where cost and turnaround matter more than peak quality.
Frequently Asked Questions
You can access GLM-5.2 by BytePlus 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-5.2 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 | $1.4 |
| Output | $4.4 |
GLM-5.2 was created by BytePlus and released on Jun 17, 2026.
GLM-5.2 supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,048 pages of text.
GLM-5.2 can generate up to 128K tokens in a single response.
GLM-5.2 accepts the following input types: text. It produces: text.
Yes, GLM-5.2 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-5.2 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 to your app without worrying about API keys or setup.
Read the Docs View Tutorials