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## Download Data
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```
wget https://raw.githubusercontent.com/openai/grade-school-math/master/grade_school_math/data/test.jsonl
```

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## Run Benchmark
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NOTE: This is an implementation for throughput/latency benchmark purposes. The prompts are not tuned to achieve good accuracy on the GSM-8K tasks.

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### Benchmark SGLang
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```
python -m sglang.launch_server --model-path meta-llama/Llama-2-7b-chat-hf --port 30000
```

```
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python3 bench_sglang.py --num-questions 32
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python3 bench_sglang.py --num-questions 16 --parallel 1
```


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### Benchmark vLLM
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```
python3 -m vllm.entrypoints.api_server --tokenizer-mode auto --model meta-llama/Llama-2-7b-chat-hf --disable-log-requests --port 21000
```

```
python3 bench_other.py --num-questions 32 --backend vllm
```


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### Benchmark LightLLM
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```
# A10G
python -m lightllm.server.api_server --tokenizer_mode auto --model_dir ~/model_weights/llama-2-7b-chat-hf --max_total_token_num 16000 --port 22000
```

```
python3 bench_other.py --num-questions 32 --backend lightllm
```


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### Benchmark Guidance
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```
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python3 bench_other.py --num-questions 8 --backend guidance --parallel 1 --n-ctx 4096 --model-path path/to/gguf
```

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### Benchmark LMQL
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```
python3 bench_other.py --num-questions 8 --backend lmql --parallel 1
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```