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