Although　deep　learning　has　reached　a　higher　accuracy　for　video　content　analysis,　it　is　not　satisfied　with　practical　application　demands　of　porn　streamer　recognition　in　live　video　because　of　multiple　parameters,　complex　structures　of　deep　network　model.　In　order　to　improve　the　recognition　efficiency　of　porn　streamer　in　live　video,　a　deep　network　model　compression　method　based　on　multimodal　knowledge　distillation　is　proposed.　First,　the　teacher　model　is　trained　with　visual-speech　deep　network　to　obtain　the　corresponding　porn　video　prediction　score.　Second,　a　lightweight　student　model　constructed　with　MobileNetV2　and　Xception　transfers　the　knowledge　from　the　teacher　model　by　using　multimodal　knowledge　distillation　strategy.　Finally,　porn　streamer　in　live　video　is　recognized　by　combining　the　lightweight　student　model　of　visualspeech　network　with　the　bullet　screen　text　recognition　network.　Experimental　results　demonstrate　that　the　proposed　method　can　effectively　drop　the　computation　cost　and　improve　the　recognition　speed　under　the　proper　accuracy.