Which language model works best your prompt? What are the biases inherent in each? Compare LLaMA2, PaLM2, OpenAI GPT-4, ChatGPT & GPT-3 engines with more LLMs being added each month.
🏃♀️Run
🔖 Examples
🚀 API
Supports ChatML & Jinja
GPT-4 Vision (openai)
GPT-4 Turbo (openai)
GPT-4 (openai)
GPT-4 32K (openai)
ChatGPT (openai)
ChatGPT 16k (openai)
Llama 2 (Meta AI)
PaLM 2 Text (Google)
PaLM 2 Chat (Google)
GPT-3.5 Davinci-3 (openai)
GPT-3.5 Davinci-2 (openai)
Curie (openai)
Babbage (openai)
Ada (openai)
⚙️ Settings
Avoid Repetition
How many answers should the copilot generate? Additional answer outputs increase the cost of each run.
The maximum number of tokens to generate in the completion. Increase to generate longer responses.
Higher values allow the LLM to take more risks. Try values larger than 1 for more creative applications or 0 to ensure that LLM gives the same answer when given the same user input.
Title
Notes
Run cost = 20 credits
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