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Optimize moe #1520
Optimize moe #1520
Conversation
Qwen1.5-MoE-A2.7B-Chat
main concurrency: 256 first_token latency(min, max, ave): 0.004s, 3.831s, 1.272s number of prompt tokens: 1148381 this pr first_token latency(min, max, ave): 0.006s, 2.110s, 0.436s number of prompt tokens: 1148381 vllm 0.4.0
== Serving Benchmark Result |
deepseek-moe-16b-chat this pr
in process vllm 0.4.0
Successful requests: 1000 |
mistralai/Mistral-7B-Instruct-v0.1 单卡 == Serving Benchmark Result == |
|
Hi, @zhulinJulia24, please help double check the inference speed |
newest code: concurrency: 256 first_token latency(min, max, ave): 0.352s, 64.760s, 14.496s number of prompt tokens: 721793 |
newest code: concurrency: 256 first_token latency(min, max, ave): 1.632s, 118.259s, 14.703s number of prompt tokens: 680073 |
newest code: concurrency: 256 first_token latency(min, max, ave): 1.181s, 61.126s, 13.595s number of prompt tokens: 741804 if I use vllm benchmark script Successful requests: 1000 |
Currently, the MOE model still has a certain gap in throughput and latency compared to vLLM. |
@zhulinJulia24 |
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LGTM
deepseek-moe-16b-chat
Qwen1.5-MoE-A2.7B-Chat TP=2
Mixtral 8x7b TP=2