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    TNG: R1T Chimera (free)Free variant

    tngtech/tng-r1t-chimera:free

    Created Nov 26, 2025163,840 context
    $0/M input tokens$0/M output tokens

    TNG-R1T-Chimera is an experimental LLM with a faible for creative storytelling and character interaction. It is a derivate of the original TNG/DeepSeek-R1T-Chimera released in April 2025 and is available exclusively via Chutes and OpenRouter.

    Characteristics and improvements include:

    We think that it has a creative and pleasant personality. It has a preliminary EQ-Bench3 value of about 1305. It is quite a bit more intelligent than the original, albeit a slightly slower. It is much more think-token consistent, i.e. reasoning and answer blocks are properly delineated. Tool calling is much improved.

    TNG Tech, the model authors, ask that users follow the careful guidelines that Microsoft has created for their "MAI-DS-R1" DeepSeek-based model. These guidelines are available on Hugging Face (https://huggingface.co/microsoft/MAI-DS-R1).

    Providers for R1T Chimera (free)

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

    Performance for R1T Chimera (free)

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    Apps using R1T Chimera (free)

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    Recent activity on R1T Chimera (free)

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    Uptime stats for R1T Chimera (free)

    Uptime stats for R1T Chimera (free) across all providers

    Sample code and API for R1T Chimera (free)

    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.