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    DeepSeek: DeepSeek V3.1

    deepseek/deepseek-chat-v3.1

    Created Aug 21, 2025131,072 context
    $0.27/M input tokens$1/M output tokens

    DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context training process, reaching up to 128K tokens, and uses FP8 microscaling for efficient inference. Users can control the reasoning behaviour with the reasoning enabled boolean. Learn more in our docs

    The model improves tool use, code generation, and reasoning efficiency, achieving performance comparable to DeepSeek-R1 on difficult benchmarks while responding more quickly. It supports structured tool calling, code agents, and search agents, making it suitable for research, coding, and agentic workflows.

    It succeeds the DeepSeek V3-0324 model and performs well on a variety of tasks.

    Providers for DeepSeek V3.1

    OpenRouter routes requests to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

    Performance for DeepSeek V3.1

    Compare different providers across OpenRouter

    Apps using DeepSeek V3.1

    Top public apps this week using this model

    Recent activity on DeepSeek V3.1

    Total usage per day on OpenRouter

    Uptime stats for DeepSeek V3.1

    Uptime stats for DeepSeek V3.1 across all providers

    Sample code and API for DeepSeek V3.1

    OpenRouter normalizes requests and responses across providers for you.

    OpenRouter provides an OpenAI-compatible completion API to 400+ models & providers that you can call directly, or using the OpenAI SDK. Additionally, some third-party SDKs are available.

    In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

    Using third-party SDKs

    For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

    See the Request docs for all possible fields, and Parameters for explanations of specific sampling parameters.