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DeepSeek

DeepSeek V4 Flash 0731

−30% vs DeepSeek
✓ Official API· served byAlibaba Cloud Model StudioAlibaba CloudDigitalOcean Serverless InferenceDigitalOcean

Served by Alibaba Cloud, which may process requests in its data centres in China.

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DeepSeek V4 Flash 0731 is the July 2026 version of DeepSeek's fast, low-cost V4 Flash model for everyday text and agent tasks, with a 1M-token context and tool calling. It thinks when you ask for reasoning and answers directly otherwise.

The real DeepSeek model

Same weights, same API, same answers. We change only how you pay for it: one key for every maker, one bill, no separate account to open. Every figure on this page comes from DeepSeek’s own page — check it.

Maker's own page

Price

input / output · per 1M tokens

The same model and the same answers through both. We choose the service for each request automatically.

Alibaba Cloud Model StudioAlibaba Cloud

−30%Only on FlintBeam

−30% on every request

Direct on Alibaba Cloud: $0.42 / $1.27

Daily discount. Today's price can change.

$0.42 / $1.27$0.30 / $0.89

DigitalOcean Serverless InferenceDigitalOcean

−30%Only on FlintBeam

−30% on every request

Direct on DigitalOcean: $0.42 / $1.27

Daily discount. Today's price can change.

$0.42 / $1.27$0.30 / $0.89

Context

1,000,000

up to 393,216 out

393,216 by default here

Modalities

ToolsReasoning

What it would cost you

1000 tokens is roughly 750 English words.

Estimated total$1.04

How it is served

Standard

Requests are retried automatically if a provider is unavailable.

Similar models

Models built for the same kind of work, at a similar price.

Eligible models may have a daily discount below the maker's price. Daily discounts apply to eligible models and can change from day to day.

Use it from your code

Model:deepseek/deepseek-v4-flash-0731
main.py
OpenAI Specification v1.0
from openai import OpenAI

# Works with the official openai package (pip install openai)
client = OpenAI(
    base_url="https://api.flintbeam.com/v1",
    api_key="sk-live-your-api-key"
)

response = client.chat.completions.create(
    model="deepseek/deepseek-v4-flash-0731",
    messages=[
        {"role": "system", "content": "You are an experienced software engineer."},
        {"role": "user", "content": "Describe the architecture of a distributed cache."}
    ],
    temperature=0.7,
    max_tokens=1500
)

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