llm-profile 0.3.0

LLM benchmarking tools for the LLM CLI

LLM Benchmarking Plugin

This is a plugin for the llm tool that adds a benchmark command to compare the performance of different language models.

The commands runs a prompt with optional system prompt for several models and compares the performance between models.

Installation

You can install the plugin using pip:

pip install llm-profile

or using llm

llm install llm-profile

Metrics

• Total time - The time taken from the request to the end of the final chunk
• Time to First Chunk - The time taken from the request to the first chunk of the response
• Length of Response - The length of the response text
• Number of Chunks - The number of chunks in the response
• Chunks per Second - The number of chunks divided by the total time taken

Benchmark Usage

To run a benchmark, provide the prompt along with any number of models using the llm alias (from llm models):

$ llm benchmark -m azure/ant-grok-3-mini -m azure/ants-gpt-4.1-mini -s "Respond in emoji" "Give me a friendly hello message" --markdown

For a single pass (no repeats) you will get a summary table:

Benchmark	Total Time	Time to First Chunk	Length of Response	Number of Chunks	Chunks per Second
azure/ant-grok-3-mini	7.79	7.76	112	30	3.85
azure/ants-gpt-4.1-mini	2.99	2.80	78	19	6.36

To repeat each benchmark and get an average of times, use the --repeat argument:

Benchmark	Total Time	Time to First Chunk	Length of Response	Number of Chunks	Chunks per Second
azure/ant-grok-3-mini	2.59 <-> 8.39 (x̄=5.49)	2.57 <-> 8.36 (x̄=5.47)	65 <-> 109 (x̄=87.00)	18 <-> 30 (x̄=24.00)	2.15 <-> 11.58 (x̄=6.86)
azure/ants-gpt-4.1-mini	0.54 <-> 2.88 (x̄=1.71)	0.26 <-> 2.69 (x̄=1.47)	76 <-> 78 (x̄=77.00)	19 <-> 19 (x̄=19.00)	6.60 <-> 35.17 (x̄=20.89)

The printout is a range (min <-> max (x̄=mean))

Providing options

You can provide key/value options for all models using the --option flag. This can be useful for setting parameters like temperature, max tokens, etc.

Example:

$ llm benchmark -m gpt-4.1-mini -m gpt-4.1-nano --option temperature 0.7 --option max_tokens 100 "Give me a friendly hello message"

This feature is also helpful for setting the seed option for reproducibility and isolating variances in time to first chunk and time to completion with the same prompt and result.

Markdown formatted results

By default, tables are printed with color showing the fastest and slowest metric in a benchmark:

If you want to customize the output, you can use the --markdown flag to get the results in a Markdown-friendly format.

Non-Streaming models

If you want to benchmark models that do not support streaming, you can use the --no-stream flag. This will disable streaming and provide a single response time.