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xc-llm-ascend/benchmarks/tests/serving-tests.json

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[
{
"test_name": "serving_qwen2_5vl_7B_tp1",
"qps_list": [
1,
4,
16,
"inf"
],
"server_parameters": {
"model": "Qwen/Qwen2.5-VL-7B-Instruct",
"tensor_parallel_size": 1,
"swap_space": 16,
"disable_log_stats": "",
"disable_log_requests": "",
"trust_remote_code": "",
"max_model_len": 16384
},
"client_parameters": {
"model": "Qwen/Qwen2.5-VL-7B-Instruct",
[Benchmark] Upgrade benchmark args for new vllm version (#3218) ### What this PR does / why we need it? Since the newest vllm commit has deprecated the arg `--endpoint-type`, we should use `--backend` instead ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? test it locally: ```shell export VLLM_USE_MODELSCOPE=true export DATASET_PATH=/root/.cache/datasets/ShareGPT_V3_unfiltered_cleaned_split.json vllm serve Qwen/Qwen2.5-7B-Instruct --load-format dummy wget -O ${DATASET_PATH} /root/.cache/datasets/ShareGPT_V3_unfiltered_cleaned_split.json https://hf-mirror.com/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json vllm bench serve --model Qwen/Qwen2.5-7B-Instruct --backend vllm --dataset-name sharegpt --dataset-path ${DATASET_PATH} --num-prompt 200 ``` and the result looks good: ```shell ============ Serving Benchmark Result ============ Successful requests: 200 Benchmark duration (s): 20.36 Total input tokens: 43560 Total generated tokens: 44697 Request throughput (req/s): 9.82 Output token throughput (tok/s): 2194.88 Peak output token throughput (tok/s): 4676.00 Peak concurrent requests: 200.00 Total Token throughput (tok/s): 4333.93 ---------------Time to First Token---------------- Mean TTFT (ms): 2143.85 Median TTFT (ms): 2486.17 P99 TTFT (ms): 2530.36 -----Time per Output Token (excl. 1st token)------ Mean TPOT (ms): 43.50 Median TPOT (ms): 30.75 P99 TPOT (ms): 309.22 ---------------Inter-token Latency---------------- Mean ITL (ms): 28.15 Median ITL (ms): 25.42 P99 ITL (ms): 38.30 ================================================== ``` - vLLM version: v0.11.0rc3 - vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0 Signed-off-by: wangli <wangli858794774@gmail.com>
2025-10-24 11:18:19 +08:00
"backend": "openai-chat",
"dataset_name": "hf",
"hf_split": "train",
"endpoint": "/v1/chat/completions",
"dataset_path": "lmarena-ai/vision-arena-bench-v0.1",
"num_prompts": 200,
"no_stream": ""
}
},
{
"test_name": "serving_qwen3_8B_tp1",
"qps_list": [
1,
4,
16,
"inf"
],
"server_parameters": {
"model": "Qwen/Qwen3-8B",
"tensor_parallel_size": 1,
"swap_space": 16,
"disable_log_stats": "",
"disable_log_requests": "",
"load_format": "dummy"
},
"client_parameters": {
"model": "Qwen/Qwen3-8B",
[Benchmark] Upgrade benchmark args for new vllm version (#3218) ### What this PR does / why we need it? Since the newest vllm commit has deprecated the arg `--endpoint-type`, we should use `--backend` instead ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? test it locally: ```shell export VLLM_USE_MODELSCOPE=true export DATASET_PATH=/root/.cache/datasets/ShareGPT_V3_unfiltered_cleaned_split.json vllm serve Qwen/Qwen2.5-7B-Instruct --load-format dummy wget -O ${DATASET_PATH} /root/.cache/datasets/ShareGPT_V3_unfiltered_cleaned_split.json https://hf-mirror.com/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json vllm bench serve --model Qwen/Qwen2.5-7B-Instruct --backend vllm --dataset-name sharegpt --dataset-path ${DATASET_PATH} --num-prompt 200 ``` and the result looks good: ```shell ============ Serving Benchmark Result ============ Successful requests: 200 Benchmark duration (s): 20.36 Total input tokens: 43560 Total generated tokens: 44697 Request throughput (req/s): 9.82 Output token throughput (tok/s): 2194.88 Peak output token throughput (tok/s): 4676.00 Peak concurrent requests: 200.00 Total Token throughput (tok/s): 4333.93 ---------------Time to First Token---------------- Mean TTFT (ms): 2143.85 Median TTFT (ms): 2486.17 P99 TTFT (ms): 2530.36 -----Time per Output Token (excl. 1st token)------ Mean TPOT (ms): 43.50 Median TPOT (ms): 30.75 P99 TPOT (ms): 309.22 ---------------Inter-token Latency---------------- Mean ITL (ms): 28.15 Median ITL (ms): 25.42 P99 ITL (ms): 38.30 ================================================== ``` - vLLM version: v0.11.0rc3 - vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0 Signed-off-by: wangli <wangli858794774@gmail.com>
2025-10-24 11:18:19 +08:00
"backend": "vllm",
"dataset_name": "sharegpt",
"dataset_path": "/github/home/.cache/datasets/ShareGPT_V3_unfiltered_cleaned_split.json",
"num_prompts": 200
}
},
{
"test_name": "serving_qwen2_5_7B_tp1",
"qps_list": [
1,
4,
16,
"inf"
],
"server_parameters": {
"model": "Qwen/Qwen2.5-7B-Instruct",
"tensor_parallel_size": 1,
"swap_space": 16,
"disable_log_stats": "",
"disable_log_requests": "",
"load_format": "dummy"
},
"client_parameters": {
"model": "Qwen/Qwen2.5-7B-Instruct",
[Benchmark] Upgrade benchmark args for new vllm version (#3218) ### What this PR does / why we need it? Since the newest vllm commit has deprecated the arg `--endpoint-type`, we should use `--backend` instead ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? test it locally: ```shell export VLLM_USE_MODELSCOPE=true export DATASET_PATH=/root/.cache/datasets/ShareGPT_V3_unfiltered_cleaned_split.json vllm serve Qwen/Qwen2.5-7B-Instruct --load-format dummy wget -O ${DATASET_PATH} /root/.cache/datasets/ShareGPT_V3_unfiltered_cleaned_split.json https://hf-mirror.com/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json vllm bench serve --model Qwen/Qwen2.5-7B-Instruct --backend vllm --dataset-name sharegpt --dataset-path ${DATASET_PATH} --num-prompt 200 ``` and the result looks good: ```shell ============ Serving Benchmark Result ============ Successful requests: 200 Benchmark duration (s): 20.36 Total input tokens: 43560 Total generated tokens: 44697 Request throughput (req/s): 9.82 Output token throughput (tok/s): 2194.88 Peak output token throughput (tok/s): 4676.00 Peak concurrent requests: 200.00 Total Token throughput (tok/s): 4333.93 ---------------Time to First Token---------------- Mean TTFT (ms): 2143.85 Median TTFT (ms): 2486.17 P99 TTFT (ms): 2530.36 -----Time per Output Token (excl. 1st token)------ Mean TPOT (ms): 43.50 Median TPOT (ms): 30.75 P99 TPOT (ms): 309.22 ---------------Inter-token Latency---------------- Mean ITL (ms): 28.15 Median ITL (ms): 25.42 P99 ITL (ms): 38.30 ================================================== ``` - vLLM version: v0.11.0rc3 - vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0 Signed-off-by: wangli <wangli858794774@gmail.com>
2025-10-24 11:18:19 +08:00
"backend": "vllm",
"dataset_name": "sharegpt",
"dataset_path": "/github/home/.cache/datasets/ShareGPT_V3_unfiltered_cleaned_split.json",
"num_prompts": 200
}
}
]