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MODEL Listed

space-bunny-alpha

Space-bunny-alpha is a high-throughput multimodal model designed for developers who require a balance of low-latency inference and deep reasoning. Unlike standard LLMs that struggle with large-scale context, this model natively supports a 1M-token window, making it ideal for codebase analysis, long-document processing, and complex RAG pipelines. A standout feature is the adjustable reasoning effort, allowing you to toggle between rapid-fire responses for simple tasks and compute-intensive logic for complex debugging or architectural planning. It handles text and visual inputs seamlessly, providing a unified interface for multimodal applications. Whether you are building autonomous agents or integrating sophisticated coding assistants, the model's architecture prioritizes speed without sacrificing the logical depth required for production-grade software engineering.

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01 / MODEL CARD

Model card

Space-bunny-alpha is a high-throughput multimodal model designed for developers who require a balance of low-latency inference and deep reasoning. Unlike standard LLMs that struggle with large-scale context, this model natively supports a 1M-token window, making it ideal for codebase analysis, long-document processing, and complex RAG pipelines. A standout feature is the adjustable reasoning effort, allowing you to toggle between rapid-fire responses for simple tasks and compute-intensive logic for complex debugging or architectural planning. It handles text and visual inputs seamlessly, providing a unified interface for multimodal applications. Whether you are building autonomous agents or integrating sophisticated coding assistants, the model's architecture prioritizes speed without sacrificing the logical depth required for production-grade software engineering.

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Providerstealth
LicenseAPI
02 / FILES & VERSIONS

Model files and versions

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Source repositoryhttps://openrouter.ai/stealth/space-bunny-alpha
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03 / DOWNLOAD

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04 / WORKFLOW

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  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

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