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    AllenAI: Olmo 3.1 32B Instruct

    allenai/olmo-3.1-32b-instruct

    Created Jan 6, 202665,536 context
    $0.20/M input tokens$0.60/M output tokens

    Olmo 3.1 32B Instruct is a large-scale, 32-billion-parameter instruction-tuned language model engineered for high-performance conversational AI, multi-turn dialogue, and practical instruction following. As part of the Olmo 3.1 family, this variant emphasizes responsiveness to complex user directions and robust chat interactions while retaining strong capabilities on reasoning and coding benchmarks. Developed by Ai2 under the Apache 2.0 license, Olmo 3.1 32B Instruct reflects the Olmo initiative’s commitment to openness and transparency.

    Providers for Olmo 3.1 32B Instruct

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

    Performance for Olmo 3.1 32B Instruct

    Compare different providers across OpenRouter

    Apps using Olmo 3.1 32B Instruct

    Top public apps this month

    Recent activity on Olmo 3.1 32B Instruct

    Total usage per day on OpenRouter

    Prompt
    30.2M
    Completion
    4.16M
    Reasoning
    0

    Prompt tokens measure input size. Reasoning tokens show internal thinking before a response. Completion tokens reflect total output length.

    Uptime stats for Olmo 3.1 32B Instruct

    Uptime stats for Olmo 3.1 32B Instruct across all providers

    Sample code and API for Olmo 3.1 32B Instruct

    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.