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  - **Dense Spatial Rewards**: Multi-objective reward function enforcing format, count, accuracy, and spatial grounding
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  - **9 Spatial Reasoning Categories**: Relations, reach, size, orientation, instance location, depth, distance, count, and existence
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  - **MoE Efficiency**: 30B total parameters with only ~3B active per token — comparable quality to dense 30B models at a fraction of the compute
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- - **Strong Zero-Shot Generalization**: Matches or beats SpatialThinker-7B on 11 of 13 evals.py benchmarks (+5pp average excluding outliers)
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  ## Inference Template
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  - **Dense Spatial Rewards**: Multi-objective reward function enforcing format, count, accuracy, and spatial grounding
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  - **9 Spatial Reasoning Categories**: Relations, reach, size, orientation, instance location, depth, distance, count, and existence
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  - **MoE Efficiency**: 30B total parameters with only ~3B active per token — comparable quality to dense 30B models at a fraction of the compute
 
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  ## Inference Template
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