DeepSeek V4.1 Flash | DeepSeek Multimodal LLM API Pricing

Name: DeepSeek V4.1 Flash API
Brand: deepseek
Price: 0.3 USD
Availability: InStock

deepseek/deepseek-v4.1-flash

Tanggal rilis: 2026-09-10

1,048,576 context · $0.30/M input tokens · $1.20/M output tokens

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...

Harga

Bayar sesuai pemakaian

Tanpa biaya di muka, bayar hanya sesuai penggunaan

Input$0.30 / M Tokens

Output$1.20 / M Tokens

Cache Read$0.0060 / M Tokens

Coba model

deepseek/deepseek-v4.1-flash

Online

Hai! Saya asisten AI yang siap membantu. Ada yang bisa saya bantu?

Siap memakai model ini di coding agent lokal?Setup agent

Penggunaan API

Gunakan contoh kode berikut untuk integrasi dengan API kami:

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 0,
});

try {
  const response = await client.chat.completions.create({
    model: 'deepseek/deepseek-v4.1-flash',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  const body = response as typeof response & { error?: { message?: string } };
  if (body.error) throw new Error(body.error.message || 'LLM generation failed');
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 0,
});

try {
  const response = await client.chat.completions.create({
    model: 'deepseek/deepseek-v4.1-flash',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  const body = response as typeof response & { error?: { message?: string } };
  if (body.error) throw new Error(body.error.message || 'LLM generation failed');
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

Pengenalan Model

DeepSeek: DeepSeek V4.1 Flash

This model is available through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.

Why It Looks Great

text+image->text architecture for Text, Image to Text workloads
1048576 context window for long prompts, document analysis, and multi-turn workflows
Vision input support for image understanding and multimodal tasks
Function calling and tool-use support for agentic application workflows
Structured output support for JSON responses and schema-constrained generation
Reasoning controls available through supported parameters

Key Features

Context Window: 1048576 tokens
Max Input: 917504 tokens
Max Output: 131072 tokens
Vision: Supported
Function Calling: Supported
Structured Outputs: Supported
Image Generation: Not listed
Audio Input: Not listed
Supported Parameters: frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, parallel_tool_calls, presence_penalty, reasoning, reasoning_effort, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_a, top_k, top_logprobs, top_p

Specifications

Specification	Value
Provider	deepseek
Model Type	Chat Completions model
Architecture	text+image->text
Context Window	1048576 tokens
Max Input	917504 tokens
Max Output	131072 tokens
Input	Text, Image
Output	Text
Vision	Supported
Function Calling	Supported
Structured Outputs	Supported
Release Date	September 10, 2026

How to Use

Write your prompt - describe the task, provide context, and specify the desired output format.
Submit - the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: deepseek/deepseek-v4.1-flash

API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="deepseek/deepseek-v4.1-flash",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "deepseek/deepseek-v4.1-flash",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: deepseek/deepseek-v4.1-flash
Provider: deepseek

Info

Penyediadeepseek

Tipellm

Fitur yang Didukung

Input

TeksGambar

Output

Teks

Konteks1,048,576

Output Maks384,000

Vision✓ Didukung

Function Calling✓ Didukung

Panduan Akses API

Base URLhttps://llm.wavespeed.ai/v1

API Endpointchat/completions

Model IDdeepseek/deepseek-v4.1-flash

Pertanyaan Umum tentang DeepSeek V4.1 Flash

Berapa biaya DeepSeek V4.1 Flash melalui API?+

Harga di WaveSpeedAI: $0.30 per juta token input dan $1.20 per juta token output. Prompt caching dan batch processing ditagih terpisah dan mengurangi biaya efektif pada beban kerja yang panjang dan berulang.

Berapa context window DeepSeek V4.1 Flash?+

DeepSeek V4.1 Flash mendukung hingga 1049K token konteks dengan hingga 384K token output per permintaan.

Apakah DeepSeek V4.1 Flash kompatibel dengan OpenAI?+

WaveSpeedAI menyediakan DeepSeek V4.1 Flash di https://llm.wavespeed.ai/v1 melalui antarmuka Chat Completions yang kompatibel dengan OpenAI. Sebagian besar klien OpenAI SDK cukup mengganti base URL dan API key; field opsional bergantung pada model.

Bagaimana memulai dengan DeepSeek V4.1 Flash?+

Masuk ke WaveSpeedAI, buat API key di Access Keys, lalu kirim permintaan ke https://llm.wavespeed.ai/v1/chat/completions dengan model id yang ditampilkan di atas. Lihat katalog model terbaru untuk ketersediaan, kemampuan, dan harga.