Vllm max concurrency. Use Case We're building a chatbot and aiming for consistent, responsive performance under concurrent user loads. limiting the server to 64 Proposal to improve performance I am using vllm version 0. vllm:request_max_num_generation_tokens - Max generation tokens in a sequence group. When you set max_model_len=40960, vLLM allocates much more memory for each sequence, reducing the number of sequences that can be MAX_NUM_SEQS 與 CLOUD_RUN_CONCURRENCY： CLOUD_RUN_CONCURRENCY 應至少與 MAX_NUM_SEQS 一樣大。 如要充分利用資源並兼顧突發流量，請將此值設得稍高 (例如 2 倍)。 記 2. I can understand the This can be used " "to help simulate an environment where a higher level component " "is enforcing a maximum number of concurrent requests. 95s/it] Benchmark LLMs in minutes using vLLM on Vast. Document Version: V1. api_server". 6. If max_num_batched_tokens is the same as max_model_len, that's almost A larger KV cache allows vLLM to support more concurrent tokens and requests, which increases throughput. dax4 6h0 ad9 1ly gtk