# MLX-LM Benchmark Tool MLX-LM Benchmark Tool is a command-line utility for measuring and comparing the performance of MLX-format language models. It generates synthetic prompt tokens and captures various performance metrics, similar to llama.cpp's llama-bench tool. ## Features - Measures multiple performance metrics: - Model load time (seconds) - Prompt token processing speed (TPS) - Generation token processing speed (TPS) - Total execution time (seconds) - Memory usage (GB) - Supports testing combinations of multiple model configurations - Customizable prompt token count and generation token count - Multiple output formats (CSV, JSON, JSONL, Markdown) - Configurable test repetitions for averaging performance ## Installation Ensure you have MLX-LM installed: ```bash pip install mlx-lm ``` ## Usage Basic usage: ```bash mlx_lm.bench -m [MODEL_PATH] -p [PROMPT_TOKENS] -n [GEN_TOKENS] -r [REPETITIONS] ``` ### Parameters - `-m, --model`: Path to the MLX model(s) to benchmark, can specify multiple (comma-separated) - `-p, --n-prompt`: Input Sequence Length (ISL), number of synthetic prompt tokens, can specify multiple (comma-separated) - `-n, --n-gen`: Output Sequence Length (OSL), number of tokens to generate, can specify multiple (comma-separated) - `-r, --repetitions`: Number of benchmark repetitions to average results over - `-o, --output-format`: Output format for benchmark results (csv, json, jsonl, md) - `-f, --output-filename`: Output filename (without extension) - `--gen-args`: Additional keyword arguments for generate() function in key=value format ## Example Benchmark two different Qwen models with different generation token counts: ```bash mlx_lm.bench -m $HOME/Files/mlx/Qwen/Qwen2.5-3B-Instruct-Q4,$HOME/Files/mlx/Qwen/Qwen2.5-7B-Instruct-Q4 -p 1 -n 16,32 -r 2 -o md ``` Sample output: | Model | Model Load Time (s) | Prompt Tokens | Prompt TPS | Response Tokens | Response TPS | Execution Time (s) | Memory Usage (GB) | |---|---|---|---|---|---|---|---| Qwen2.5-3B-Instruct-Q4 | 0.469 | 1 | 140.084 | 16 | 184.93 | 0.094 | 1.75 | Qwen2.5-3B-Instruct-Q4 | 0.469 | 1 | 137.294 | 32 | 178.829 | 0.186 | 1.75 | Qwen2.5-7B-Instruct-Q4 | 0.537 | 1 | 110.817 | 16 | 139.308 | 0.124 | 6.02 | Qwen2.5-7B-Instruct-Q4 | 0.537 | 1 | 109.005 | 32 | 134.764 | 0.247 | 6.02 | ## Advanced Usage Run more complex benchmarks: ```bash # Test multiple models with various prompt and generation length combinations mlx_lm.bench -m path/to/model1,path/to/model2 -p 1,8,64,128 -n 16,128,512 -r 3 -o json -f detailed_results # Pass additional arguments to the generation function mlx_lm.bench -m path/to/model -p 128 -n 128 -r 3 --gen-args kv_group_size=64 ``` ## Output Metrics Benchmark results include the following metrics: - **Model**: Path of the model being tested - **Model Load Time (s)**: Time required to load the model (seconds) - **Prompt Tokens**: Number of prompt tokens processed - **Prompt TPS**: Prompt token processing speed (tokens per second) - **Response Tokens**: Number of response tokens generated - **Response TPS**: Response token generation speed (tokens per second) - **Execution Time (s)**: Total execution time (seconds) - **Memory Usage (GB)**: Peak memory usage (GB)