BytePlus: DeepSeek V3.2
byteplus/deepseek-v3-2-251201
Access DeepSeek V3.2 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/deepseek-v3-2-251201"
}).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/deepseek-v3-2-251201"
}).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/deepseek-v3-2-251201",
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/deepseek-v3-2-251201",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
DeepSeek V3.2 is a mixture-of-experts large language model from DeepSeek, made available here through BytePlus's Model Ark hosting.
It uses DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism that lowers compute cost while preserving quality on long-context tasks, and it supports tool use in both thinking and non-thinking modes.
DeepSeek describes its reasoning performance as in the same class as GPT-5, trained with a large-scale agentic data synthesis pipeline spanning over 1,800 environments and more than 85,000 complex instructions to strengthen tool-use in agentic settings.
It's suited for reasoning-heavy work such as math and coding, and for agentic applications that call tools as part of multi-step tasks, while balancing inference speed against the deeper reasoning of DeepSeek's higher-compute Speciale variant.
Context Window 128K
tokens
Max Output 32K
tokens
Input Cost $0.28
per million tokens
Output Cost $0.42
per million tokens
Input text
modalities
Tool Use Yes
Release Date Dec 1, 2025
Model Playground
Try DeepSeek V3.2 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From BytePlus
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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.
ChatGLM-5.2
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.
Frequently Asked Questions
You can access DeepSeek V3.2 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 DeepSeek V3.2 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 | $0.28 |
| Output | $0.42 |
DeepSeek V3.2 was created by BytePlus and released on Dec 1, 2025.
DeepSeek V3.2 supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.
DeepSeek V3.2 can generate up to 32K tokens in a single response.
DeepSeek V3.2 accepts the following input types: text. It produces: text.
Yes, DeepSeek V3.2 supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the DeepSeek V3.2 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 DeepSeek V3.2 to your app without worrying about API keys or setup.
Read the Docs View Tutorials