Optimizing Qwen3-235B-A22B Throughput on NVIDIA H100 GPUs
Conclusion
Recommended configuration for optimizing throughput of Qwen3-235B-A22B-Instruct-2507 on H100 GPUs:
Serving Command
vllm serve Qwen/Qwen3-235B-A22B-Instruct-2507-FP8 -tp 4 --max-num-batched-tokens 16384
Comparison of benchmark results before and after optimization:
| Benchmark Case | baseline (vLLM without any optimizations) | Optimized |
|---|---|---|
| ShareGPT | Total TPS: 8424.86 Mean TPOT(ms): 147.56 |
Total TPS: 7787.17x2 (+84.9%) Mean TPOT(ms): 186.26 |
| Short Prompt | Total TPS: 14668.27 Mean TPOT(ms): 212.98 |
Total TPS: 21211.83x2 (+189.2%) Mean TPOT(ms): 125.18 |
| Medium Prompt | Total TPS: 23858.69 Mean TPOT(ms): 101.08 |
Total TPS: 18950.04x2 (+58.9%) Mean TPOT(ms): 125.93 |
| Long Prompt | Total TPS: 21113.53 Mean TPOT(ms): 68.94 |
Total TPS: 16478.79x2 (+56.1%) Mean TPOT(ms): 89.52 |
| Very Long Prompt | Total TPS: 22657.51 Mean TPOT(ms): 132.10 |
Total TPS: 15366.32x2 (+35.6%) Mean TPOT(ms): 194.60 |
Note
- Our benchmark tests do not cover all possible optimization combinations. For example, we select the inference engine that performs best under its default configuration as the starting point for further tuning. This pruning approach yields a local optimum, which may not be the global optimum.
- There are other optimization methods that depend on specific user scenarios, including max batch size, schedule configuration, extended KV cache, CUDA graph, Torch Compile, etc. The conclusions in this document can serve as a starting point for more targeted optimizations.
- The tests are conducted on specific hardware and software setups. Advances in the inference engine may lead to new conclusions.
- Although using quantization may impact accuracy. FP8 quantization can achieves less than 1% accuracy drop for most models. See the evaluation results for more details. Therefore, it is highly recommended to use FP8 quantization for high-throughput serving scenarios.
If there are any missing points or updates reflecting new changes, please let us know.
Optimization Objective
Achieve high throughput under high-concurrency request scenarios.
Experimental Setup
Model
Qwen3-235B-A22B-Instruct-2507
Hardware
NVIDIA H100 GPUs
Engine Version
- vLLM: v0.11.0
- SGLang: v0.5.5.post1
Benchmark Dataset
- ShareGPT
- Random dataset with varying sequence lengths:
- Very long prompt: 32000 input tokens, 100 output tokens
- Long prompt: 4000 input tokens, 200 output tokens
- Medium prompt: 2000 input tokens, 100 output tokens
- Short prompt: 128 input tokens, 4 output tokens
Benchmark Script
We use the vLLM bench CLI tool to benchmark the model performance. The following command is used to run the benchmark:
# Prepare the ShareGPT dataset
wget https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json
# Benchmark on ShareGPT dataset
vllm bench serve --model Qwen/Qwen3-235B-A22B-Instruct-2507 --backend openai-chat --endpoint /v1/chat/completions --dataset-name sharegpt --dataset-path ShareGPT_V3_unfiltered_cleaned_split.json --num-prompts 1000
# Benchmark on random dataset (fixed seed for reproducibility)
vllm bench serve --model Qwen/Qwen3-235B-A22B-Instruct-2507 --backend openai-chat --endpoint /v1/chat/completions --dataset-name random --random-input-len 4000 --random-output-len 200 --num-prompts 500 --seed 42
Experiment Results
1. Choosing the Inference Engine
vLLM
Serving script
vllm serve Qwen/Qwen3-235B-A22B-Instruct-2507 -tp 8
Benchmark result
============ Serving Benchmark Result ============
Successful requests: 984
Benchmark duration (s): 48.28
Total input tokens: 212894
Total generated tokens: 193865
Request throughput (req/s): 20.38
Output token throughput (tok/s): 4015.36
Peak output token throughput (tok/s): 9638.00
Peak concurrent requests: 984.00
Total Token throughput (tok/s): 8424.86
---------------Time to First Token----------------
Mean TTFT (ms): 8730.69
Median TTFT (ms): 8707.89
P99 TTFT (ms): 12940.37
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 147.56
Median TPOT (ms): 114.67
P99 TPOT (ms): 342.35
---------------Inter-token Latency----------------
Mean ITL (ms): 81.31
Median ITL (ms): 51.14
P99 ITL (ms): 677.61
==================================================
SGLang
Serving script
python3 -m sglang.launch_server --model-path Qwen/Qwen3-235B-A22B-Instruct-2507 --tp-size 8
Benchmark result
============ Serving Benchmark Result ============
Successful requests: 984
Benchmark duration (s): 53.18
Total input tokens: 214137
Total generated tokens: 193829
Request throughput (req/s): 18.50
Output token throughput (tok/s): 3644.72
Peak output token throughput (tok/s): 8791.00
Peak concurrent requests: 984.00
Total Token throughput (tok/s): 7671.31
---------------Time to First Token----------------
Mean TTFT (ms): 11715.28
Median TTFT (ms): 6274.12
P99 TTFT (ms): 32860.14
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 178.35
Median TPOT (ms): 102.70
P99 TPOT (ms): 841.80
---------------Inter-token Latency----------------
Mean ITL (ms): 88.35
Median ITL (ms): 44.39
P99 ITL (ms): 732.90
==================================================
Result: vLLM (8424.86 tok/s) > SGLang (7671.31 tok/s)
2. Quantization in vLLM
Serving script
# TP8 only is not compatible with the model weight. Use EP as well.
vllm serve Qwen/Qwen3-235B-A22B-Instruct-2507-FP8 -tp 8 --enable-expert-parallel
Benchmark result
============ Serving Benchmark Result ============
Successful requests: 984
Benchmark duration (s): 49.88
Total input tokens: 211761
Total generated tokens: 192350
Request throughput (req/s): 19.73
Output token throughput (tok/s): 3856.59
Peak output token throughput (tok/s): 9788.00
Peak concurrent requests: 984.00
Total Token throughput (tok/s): 8102.36
---------------Time to First Token----------------
Mean TTFT (ms): 9755.64
Median TTFT (ms): 9742.53
P99 TTFT (ms): 14508.64
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 169.52
Median TPOT (ms): 129.08
P99 TPOT (ms): 353.11
---------------Inter-token Latency----------------
Mean ITL (ms): 88.39
Median ITL (ms): 49.03
P99 ITL (ms): 343.14
==================================================
3. Parallelism in vLLM
TP4
Serving script
vllm serve Qwen/Qwen3-235B-A22B-Instruct-2507-FP8 -tp 4
Benchmark result
============ Serving Benchmark Result ============
Successful requests: 984
Benchmark duration (s): 54.12
Total input tokens: 212992
Total generated tokens: 194446
Request throughput (req/s): 18.18
Output token throughput (tok/s): 3592.57
Peak output token throughput (tok/s): 8605.00
Peak concurrent requests: 984.00
Total Token throughput (tok/s): 7527.80
---------------Time to First Token----------------
Mean TTFT (ms): 9924.69
Median TTFT (ms): 9896.14
P99 TTFT (ms): 15574.61
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 169.20
Median TPOT (ms): 121.96
P99 TPOT (ms): 372.71
---------------Inter-token Latency----------------
Mean ITL (ms): 89.89
Median ITL (ms): 57.15
P99 ITL (ms): 351.02
==================================================
TP4+EP
Serving script
vllm serve Qwen/Qwen3-235B-A22B-Instruct-2507-FP8 -tp 4 --enable-expert-parallel
Benchmark result
============ Serving Benchmark Result ============
Successful requests: 984
Benchmark duration (s): 57.08
Total input tokens: 214311
Total generated tokens: 192752
Request throughput (req/s): 17.24
Output token throughput (tok/s): 3376.99
Peak output token throughput (tok/s): 8005.00
Peak concurrent requests: 984.00
Total Token throughput (tok/s): 7131.69
---------------Time to First Token----------------
Mean TTFT (ms): 10706.10
Median TTFT (ms): 10676.53
P99 TTFT (ms): 17226.88
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 190.24
Median TPOT (ms): 131.62
P99 TPOT (ms): 432.31
---------------Inter-token Latency----------------
Mean ITL (ms): 96.98
Median ITL (ms): 60.65
P99 ITL (ms): 408.09
==================================================
4. Attention Backend in vLLM
FlashAttention is the default.
FlashInfer
Serving script
VLLM_ATTENTION_BACKEND=FLASHINFER vllm serve Qwen/Qwen3-235B-A22B-Instruct-2507-FP8 -tp 4
Benchmark result
# Crash
XFormers
Serving script
VLLM_ATTENTION_BACKEND=XFORMERS vllm serve Qwen/Qwen3-235B-A22B-Instruct-2507-FP8 -tp 4
Benchmark result
# Crash on inference
5. Max Number of Batched Tokens in vLLM
Serving script
vllm serve Qwen/Qwen3-235B-A22B-Instruct-2507-FP8 -tp 4 --max-num-batched-tokens 16384
Benchmark result
# --max-num-batched-tokens 16384
============ Serving Benchmark Result ============
Successful requests: 984
Benchmark duration (s): 52.46
Total input tokens: 214381
Total generated tokens: 194148
Request throughput (req/s): 18.76
Output token throughput (tok/s): 3700.75
Peak output token throughput (tok/s): 8574.00
Peak concurrent requests: 984.00
Total Token throughput (tok/s): 7787.17
---------------Time to First Token----------------
Mean TTFT (ms): 9600.73
Median TTFT (ms): 9525.78
P99 TTFT (ms): 13887.13
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 186.26
Median TPOT (ms): 108.31
P99 TPOT (ms): 634.48
---------------Inter-token Latency----------------
Mean ITL (ms): 86.62
Median ITL (ms): 56.97
P99 ITL (ms): 632.37
==================================================
# --max-num-batched-tokens 32768
# Crash on inference
Summary of Optimization Options
| Optimization Option | Throughput Improvement |
|---|---|
| Engine Selection | - |
| Quantization | - |
| Parallelism | +78.7% |
| Attention Backend | - |
| Max Number of Batched Tokens | +3.4% |
Other Benchmark Cases
We further benchmarked the optimized configuration to evaluate its generalization under various workloads.
Baseline serving script
vllm serve Qwen/Qwen3-235B-A22B-Instruct-2507 -tp 8
Baseline benchmark results
# random 32K input
============ Serving Benchmark Result ============
Successful requests: 100
Benchmark duration (s): 141.60
Total input tokens: 3200000
Total generated tokens: 8191
Request throughput (req/s): 0.71
Output token throughput (tok/s): 57.85
Peak output token throughput (tok/s): 346.00
Peak concurrent requests: 100.00
Total Token throughput (tok/s): 22657.51
---------------Time to First Token----------------
Mean TTFT (ms): 70409.55
Median TTFT (ms): 70737.29
P99 TTFT (ms): 138084.17
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 132.10
Median TPOT (ms): 134.49
P99 TPOT (ms): 182.76
---------------Inter-token Latency----------------
Mean ITL (ms): 129.44
Median ITL (ms): 23.29
P99 ITL (ms): 376.34
==================================================
# random 4K input
============ Serving Benchmark Result ============
Successful requests: 500
Benchmark duration (s): 98.99
Total input tokens: 1997942
Total generated tokens: 92185
Request throughput (req/s): 5.05
Output token throughput (tok/s): 931.21
Peak output token throughput (tok/s): 2450.00
Peak concurrent requests: 500.00
Total Token throughput (tok/s): 21113.53
---------------Time to First Token----------------
Mean TTFT (ms): 47811.58
Median TTFT (ms): 48562.54
P99 TTFT (ms): 93161.32
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 68.94
Median TPOT (ms): 72.58
P99 TPOT (ms): 92.94
---------------Inter-token Latency----------------
Mean ITL (ms): 68.75
Median ITL (ms): 30.18
P99 ITL (ms): 245.68
==================================================
# random 2K input
============ Serving Benchmark Result ============
Successful requests: 500
Benchmark duration (s): 43.91
Total input tokens: 998175
Total generated tokens: 49500
Request throughput (req/s): 11.39
Output token throughput (tok/s): 1127.26
Peak output token throughput (tok/s): 4021.00
Peak concurrent requests: 500.00
Total Token throughput (tok/s): 23858.69
---------------Time to First Token----------------
Mean TTFT (ms): 21313.79
Median TTFT (ms): 20242.32
P99 TTFT (ms): 40939.00
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 101.08
Median TPOT (ms): 108.64
P99 TPOT (ms): 125.24
---------------Inter-token Latency----------------
Mean ITL (ms): 100.16
Median ITL (ms): 35.94
P99 ITL (ms): 244.64
==================================================
# random 128 input
============ Serving Benchmark Result ============
Successful requests: 984
Benchmark duration (s): 8.83
Total input tokens: 125650
Total generated tokens: 3936
Request throughput (req/s): 111.38
Output token throughput (tok/s): 445.53
Peak output token throughput (tok/s): 1489.00
Peak concurrent requests: 984.00
Total Token throughput (tok/s): 14668.27
---------------Time to First Token----------------
Mean TTFT (ms): 7042.17
Median TTFT (ms): 6882.45
P99 TTFT (ms): 8721.24
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 212.98
Median TPOT (ms): 238.84
P99 TPOT (ms): 242.28
---------------Inter-token Latency----------------
Mean ITL (ms): 159.73
Median ITL (ms): 235.21
P99 ITL (ms): 250.35
==================================================
Optimized serving script
vllm serve Qwen/Qwen3-235B-A22B-Instruct-2507-FP8 -tp 4 --max-num-batched-tokens 16384
Optimized benchmark results
# random 32K input
============ Serving Benchmark Result ============
Successful requests: 100
Benchmark duration (s): 208.79
Total input tokens: 3200000
Total generated tokens: 8281
Request throughput (req/s): 0.48
Output token throughput (tok/s): 39.66
Peak output token throughput (tok/s): 277.00
Peak concurrent requests: 100.00
Total Token throughput (tok/s): 15366.32
---------------Time to First Token----------------
Mean TTFT (ms): 103754.50
Median TTFT (ms): 103784.48
P99 TTFT (ms): 205204.25
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 194.60
Median TPOT (ms): 194.50
P99 TPOT (ms): 277.94
---------------Inter-token Latency----------------
Mean ITL (ms): 193.15
Median ITL (ms): 27.60
P99 ITL (ms): 1117.34
==================================================
# random 4K input
============ Serving Benchmark Result ============
Successful requests: 500
Benchmark duration (s): 126.76
Total input tokens: 1997942
Total generated tokens: 90966
Request throughput (req/s): 3.94
Output token throughput (tok/s): 717.60
Peak output token throughput (tok/s): 2139.00
Peak concurrent requests: 500.00
Total Token throughput (tok/s): 16478.79
---------------Time to First Token----------------
Mean TTFT (ms): 60513.14
Median TTFT (ms): 61048.35
P99 TTFT (ms): 120001.31
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 89.52
Median TPOT (ms): 94.78
P99 TPOT (ms): 121.95
---------------Inter-token Latency----------------
Mean ITL (ms): 89.17
Median ITL (ms): 34.82
P99 ITL (ms): 642.94
==================================================
# random 2K input
============ Serving Benchmark Result ============
Successful requests: 500
Benchmark duration (s): 55.28
Total input tokens: 998175
Total generated tokens: 49471
Request throughput (req/s): 9.04
Output token throughput (tok/s): 894.84
Peak output token throughput (tok/s): 3723.00
Peak concurrent requests: 500.00
Total Token throughput (tok/s): 18950.04
---------------Time to First Token----------------
Mean TTFT (ms): 26860.95
Median TTFT (ms): 26155.54
P99 TTFT (ms): 51773.01
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 125.93
Median TPOT (ms): 140.65
P99 TPOT (ms): 152.49
---------------Inter-token Latency----------------
Mean ITL (ms): 124.89
Median ITL (ms): 39.21
P99 ITL (ms): 632.84
==================================================
# random 128 input
============ Serving Benchmark Result ============
Successful requests: 984
Benchmark duration (s): 6.11
Total input tokens: 125650
Total generated tokens: 3936
Request throughput (req/s): 161.07
Output token throughput (tok/s): 644.28
Peak output token throughput (tok/s): 3676.00
Peak concurrent requests: 984.00
Total Token throughput (tok/s): 21211.83
---------------Time to First Token----------------
Mean TTFT (ms): 5621.51
Median TTFT (ms): 5525.90
P99 TTFT (ms): 5803.57
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms): 125.18
Median TPOT (ms): 152.34
P99 TPOT (ms): 182.84
---------------Inter-token Latency----------------
Mean ITL (ms): 93.89
Median ITL (ms): 110.55
P99 ITL (ms): 243.41
==================================================