[GH-ISSUE #129] Significant Discrepancies Between Batch Inference and Single Inference in DeepSeekVL2 #108

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opened 2026-10-26 21:12:06 +00:00 by bsakaguchi · 0 comments
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Originally created by @j1ajunzhu on GitHub (Apr 8, 2025).
Original GitHub issue: https://github.com/deepseek-ai/DeepSeek-VL2/issues/129

Description:
I've noticed that when using DeepSeekVL2-tiny, predictions for the same input differ significantly between single inference (processing one input at a time) and batch inference (processing multiple inputs together). The outputs for a single item in a batch are notably different from its output when run alone. I suspect this might relate to how batch normalization or dropout is handled, or a difference in how the data is preprocessed. Any guidance on why this discrepancy occurs, or how to align the results, would be greatly appreciated.

Originally created by @j1ajunzhu on GitHub (Apr 8, 2025). Original GitHub issue: https://github.com/deepseek-ai/DeepSeek-VL2/issues/129 **Description:** I've noticed that when using DeepSeekVL2-tiny, predictions for the same input differ significantly between single inference (processing one input at a time) and batch inference (processing multiple inputs together). The outputs for a single item in a batch are notably different from its output when run alone. I suspect this might relate to how batch normalization or dropout is handled, or a difference in how the data is preprocessed. Any guidance on why this discrepancy occurs, or how to align the results, would be greatly appreciated.
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deepseek-ai/DeepSeek-VL2#108
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