DeepSeek V4.1 Flash

Chat Completions

deepseek-v4.1-flash

Deepseek|Created Sep 10, 2026|1.0M context

Chat Completions

DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters on input and 16B on output from a 552B-parameter backbone, an asymmetric split that keeps per-token compute low relative to the model's total size. Image understanding is native to the architecture, with visual and text embeddings trained jointly from the start of pre-training rather than added afterward as in the earlier experimental V4 Flash Vision Exp.

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-v4.1-flash",
    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 PenaltyLogit BiasMax Completion TokensParallel Tool CallsPresence PenaltyReasoning EffortResponse FormatStopTemperatureTool ChoiceToolsTop PLogprobsPrediction