DeepSeek V4 Pro 0423

Chat Completions

deepseek-v4-pro

Deepseek|Created Apr 24, 2026|1.0M context

Chat Completions

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B active parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding, and long-horizon agent workflows, delivering strong results across knowledge, mathematics, and software engineering benchmarks. Built on the same architecture as DeepSeek V4 Flash, it adds a hybrid attention system for efficient long-context processing and supports multiple reasoning modes to balance speed and depth based on the task. It is well suited for demanding workloads such as full-codebase analysis, multi-step automation, and large-scale information synthesis, where both performance and efficiency are essential.

Overview Specifications Activity Performance Uptime Examples API Reference

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Pricing-50%

Pay-as-you-go rates for this model. More details in the billing guide.

Input Tokens (1M)

$0.43

Cached Input Tokens (1M)

$0.04

Output Tokens (1M)

$0.87

Capabilities

Input Modalities

Text

Output Modalities

Text

Supported Parameters

Available parameters for API requests

Max Completion TokensPresence PenaltyResponse FormatTemperatureTool ChoiceToolsTop PFrequency PenaltyParallel Tool CallsStopLogit BiasReasoning EffortLogprobsPrediction

Usage Analytics

Token usage of this model on our platform

Throughput

Time-To-First-Token (TTFT)

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-pro",
    messages=[
        {"role": "user", "content": "What's 2+2?"}
    ],
    temperature=0.2,
)
print(resp.choices[0].message.content)