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    Deep Cogito: Cogito v2.1 671B

    deepcogito/cogito-v2.1-671b

    Created Nov 13, 2025128,000 context
    $1.25/M input tokens$1.25/M output tokens

    Cogito v2.1 671B MoE represents one of the strongest open models globally, matching performance of frontier closed and open models. This model is trained using self play with reinforcement learning to reach state-of-the-art performance on multiple categories (instruction following, coding, longer queries and creative writing). This advanced system demonstrates significant progress toward scalable superintelligence through policy improvement.

    Providers for Cogito v2.1 671B

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

    Performance for Cogito v2.1 671B

    Compare different providers across OpenRouter

    Apps using Cogito v2.1 671B

    Top public apps this week using this model

    Recent activity on Cogito v2.1 671B

    Total usage per day on OpenRouter

    Uptime stats for Cogito v2.1 671B

    Uptime stats for Cogito v2.1 671B across all providers

    Sample code and API for Cogito v2.1 671B

    OpenRouter normalizes requests and responses across providers for you.

    OpenRouter supports reasoning-enabled models that can show their step-by-step thinking process. Use the reasoning parameter in your request to enable reasoning, and access the reasoning_details array in the response to see the model's internal reasoning before the final answer. When continuing a conversation, preserve the complete reasoning_details when passing messages back to the model so it can continue reasoning from where it left off. Learn more about reasoning tokens.

    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.