Model ID
vultr/VultronRetrieverPrime-Qwen3.5-8B
Capabilities
VultronRetrieverPrime Qwen3.5 8B
VultronRetrieverPrime Qwen3.5 8B is a multimodal late-interaction retrieval model designed for visual document search and multilingual RAG across PDFs, scans, slides, and reports. It features 8B parameters, using a 32-layer hybrid GatedDeltaNet and full-attention architecture with 4,096 hidden size, 16 attention heads, and 320-dimensional multi-vector embeddings with MaxSim scoring. Supporting up to 262K context and 1,792 visual tokens, it delivers state-of-the-art retrieval accuracy while maintaining a compact index and efficient large-scale serving.
About this model
VultronRetrieverPrime Qwen3.5 8B is a multimodal late-interaction retrieval model designed for visual document search and multilingual RAG across PDFs, scans, slides, and reports. It features 8B parameters, using a 32-layer hybrid GatedDeltaNet and full-attention architecture with 4,096 hidden size, 16 attention heads, and 320-dimensional multi-vector embeddings with MaxSim scoring. Supporting up to 262K context and 1,792 visual tokens, it delivers state-of-the-art retrieval accuracy while maintaining a compact index and efficient large-scale serving.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (vultr/VultronRetrieverPrime-Qwen3.5-8B). Released under Apache 2.0.
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Hardware
MI325X
2,048 GB
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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AMD Instinct MI325X
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