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    Models/Image Text To Text/Jackrong/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled

    Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled

    by Jackrong

    128Kdl/month
    60likes
    Identifier
    Model ID
    Jackrong/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled

    Tags

    safetensorsqwen3_5unslothqwenqwen3.5reasoningchain-of-thoughtloraimage-text-to-textconversationalenzhkodataset:Jackrong/Qwen3.5-reasoning-700xdataset:nohurry/Opus-4.6-Reasoning-3000x-filteredbase_model:Qwen/Qwen3.5-9Bbase_model:adapter:Qwen/Qwen3.5-9Blicense:apache-2.0region:us

    Use Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled on Mixpeek

    Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.

    Open Studio

    How It Runs on Mixpeek

    On Mixpeek, Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled runs as a managed extractor inside a processing pipeline. Point a bucket of image text to text data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.

    Extractor outputs land in the Mixpeek Vector Store (MVS), where you can combine them with retrieval, reranking, and filter stages to build end-to-end search and agent-perception pipelines, no model-serving infrastructure to maintain.