Model Marketplace

DeepSeek

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Overview

DeepSeek-V4.1-Flash-1017 is the latest iteration of V4.1-Flash, trained with self-feedback-based reinforcement learning to deliver substantial gains over its predecessor across benchmarks such as Terminal-Bench 4.0, DeepSWE v1.1, and ProgramBench, while shortening task runtime and output length to reach a new performance–cost Pareto optimum across multiple harnesses. Its ability to build complete projects from scratch is further strengthened, enabling "wish-based" programming tasks such as game development and 3D modeling, while retaining the same 552B-parameter MoE, native multimodal visual understanding, 1M-token context window, and 384K-token maximum output.

Input

TextImage

Output

Text

Features

Prefix Completion

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Asynchronously process requests in batches to reduce costs.View docs

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

Fine-tuning

Train models on sample data to better adapt them to specific tasks.View docs

Pricing

Off-peak hours are 22:00 to 08:00 (next day) in UTC+8; other times are peak hours.
  • Input
    $0.15Per 1M tokens
  • Output
    $0.6Per 1M tokens
  • Input(Implicit Cache)
    $0.015Per 1M tokens

Rate Limits & Context

  • Max Input
    1M
  • Max Output
    393K
  • Max Input (Thinking)
    1M
  • Max Output (Thinking)
    393K
  • Context
    1M
  • Max Reasoning
    393K
  • TPMTokens Per Minute
    1M
  • RPMRequests Per Minute
    15K

Built-in Tools

code_interpreterResponses API
web_extractorResponses API
web_searchResponses API
web_searchAnthropic API
web_fetchAnthropic API

API Reference

Call API
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import os
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://ap-southeast-1.maas.qwencloudapi.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="deepseek-v4.1-flash-1017",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "image_url", "image_url": {"url": "https://example.com/image.jpg"}},
                {"type": "text", "text": "Please only output the text content in the image."},
            ],
        }
    ],
)
print(completion.choices[0].message.content)