Prompt Input Section
Advanced Settings
Model Comparison Results
gpt-4.1
Ready to run
gpt-4.1-mini
Ready to run
gpt-4.1-nano
Ready to run
gpt-4o
Ready to run
gpt-4o-mini
Ready to run
o1
Ready to run
o4-mini
Ready to run
o3-mini
Ready to run
o1-mini
Ready to run
🧠FAQ: PickLLM OpenAI Model Results Comparison
What is PickLLM?
PickLLM is a single-page app that lets you compare responses from multiple OpenAI models side by side. You enter a prompt, and the selected models generate responses in parallel.
To use the tool, you must provide your own OpenAI API key. Your key is stored only in your browser's local storage and is never saved on any server. Requests are proxied through Next.js API routes for security, but your key is only used to make direct requests to OpenAI servers.
What models are supported?
By default, PickLLM loads the following 9 models:
'gpt-4.1','gpt-4.1-mini','gpt-4.1-nano','gpt-4o','gpt-4o-mini','o1','o4-mini','o3-mini','o1-mini'However, you can fully customize the list in Advanced Settings — add or remove models as needed.
Can I compare multiple models at once?
Yes. There is no hardcoded limit. The default setup compares 9 models, but you can freely add or remove any number of models depending on your needs.
What advanced settings are available?
You can optionally set per-model configuration:
- Temperature (0–2): Controls response randomness.
- Top P (0–1): Controls nucleus sampling.
- Max Tokens (default 1024): Caps the response length.
Only some models support temperature and top_p — others will ignore those values.
Which models support advanced settings?
The following models support both
temperature
andtop_p
:['gpt-4.1', 'gpt-4.1-mini', 'gpt-4.1-nano', 'gpt-4o', 'gpt-4o-mini']Other models (e.g.,
o1
,o3-mini
,o4-mini
) only supportmax_completion_tokens
.Is my API key safe?
Yes. Your API key is stored only in your browser's local storage and is never saved on any server. All requests are proxied through Next.js API routes for security, but your key is only used to make direct requests to OpenAI servers.
Who is PickLLM for?
- Prompt engineers testing variations
- AI product teams benchmarking models
- Developers exploring behavior differences
- Hobbyists experimenting with prompt design