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    Models/Image Text To Text/rdtand/Qwen3.6-35B-A3B-PrismaQuant-4.75bit-vllm
    Image Text To Textvllmapache-2.0

    Qwen3.6-35B-A3B-PrismaQuant-4.75bit-vllm

    by rdtand

    99Kdl/month
    35likes
    Identifier
    Model ID
    rdtand/Qwen3.6-35B-A3B-PrismaQuant-4.75bit-vllm

    Tags

    vllmsafetensorsqwen3_5_moeqwen3.6moevision-languagemultimodaldeltanetquantizedmixed-precisionnvfp4mxfp8compressed-tensorsprismaquantmtpspeculative-decodingimage-text-to-textconversationalenmultilingualbase_model:Qwen/Qwen3.6-35B-A3Bbase_model:quantized:Qwen/Qwen3.6-35B-A3Blicense:apache-2.08-bitregion:us

    Use Qwen3.6-35B-A3B-PrismaQuant-4.75bit-vllm 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, Qwen3.6-35B-A3B-PrismaQuant-4.75bit-vllm 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.