Deepseek v3.2

Chat Completions

deepseek-v3.2

Deepseek|Created Dec 1, 2025|163.8k context

Chat Completions

DeepSeek-V3.2 is a large language model optimized for high computational efficiency and strong tool-use reasoning. It features DeepSeek Sparse Attention (DSA), a mechanism that lowers training and inference costs while maintaining quality in long-context tasks. A scalable reinforcement learning post-training framework further enhances reasoning, achieving performance comparable to GPT-5 and earning top results on the 2025 IMO and IOI. V3.2 also leverages large-scale agentic task synthesis to improve reasoning in practical tool-use scenarios, boosting its generalization and compliance in interactive environments.

Overview Specifications Activity Performance Uptime Examples API Reference

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Endpoints and request shape

This page collects the public integration surface for the model: supported endpoints, available request parameters, and example calls through the NagaAI API.

Chat Completions

Code Example

Example code for using this model through our API with Python (OpenAI SDK) or cURL. Replace placeholders with your API key and model ID.

Basic request example. Ensure API key permissions. For more details, see our documentation.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.naga.ac/v1",
    api_key="YOUR_API_KEY",
)

resp = client.chat.completions.create(
    model="deepseek-v3.2",
    messages=[
        {"role": "user", "content": "What's 2+2?"}
    ],
    temperature=0.2,
)
print(resp.choices[0].message.content)

Supported Parameters

Available parameters for API requests

Frequency PenaltyMax Completion TokensPresence PenaltyResponse FormatReasoning EffortStopTemperatureTool ChoiceToolsTop PLogit BiasLogprobsParallel Tool CallsPrediction