When creating an agent with Play.ai, you have the flexibility to choose from a variety of language models to power your agent’s intelligence. This customization allows you to tailor your agent’s capabilities to your specific needs, and have fun experimenting! Let’s explore the options and their pros and cons.

Available Models

Play.ai offers a range of models, including:

  • GPT models (e.g., gpt-4o, gpt-4o-mini, gpt-3.5-turbo, gpt-4, gpt-4-turbo)
  • Llama models (e.g., llama3-70b-8192, llama3-8b-8192)
  • Hermes models (e.g., hermes-3-llama-3.1-405b-fp8, hermes-3-llama-3.1-405b-fp8-128k)
  • Gemma models (e.g., gemma-7b-it, gemma2-9b-it)
  • Mixtral model (mixtral-8x7b-32768)

Each model has its own strengths and trade-offs, which we’ll discuss below.

Pros and Cons of Different Model Types

GPT Models

Pros:

  • High-quality outputs and strong general knowledge
  • Excellent at understanding context and nuance
  • Constantly updated with new information

Cons:

  • May have longer response times for larger models (e.g., GPT-4)
  • Can be overly formal and assistant like.

Llama Models

Pros:

  • Various sizes available to balance performance and speed
  • More conversational, funny, and creative
  • Some versions optimized for specific tasks (e.g., tool use)

Cons:

  • May not have as broad knowledge as GPT models
  • Performance can vary depending on the specific version and task
  • Generally less accurate at action execution than gpt models. And

Hermes Models

Pros:

  • Optimized for conversational use cases
  • Based on Llama architecture with additional training on massive conversational datasets

Cons:

  • May be less versatile than more general-purpose models
  • Limited availability of different sizes and variants
  • Larger model -> higher latency
  • No support for actions

Choosing the Right Model

We’re still very early in the world of AI and LLMS. There is no “one size fits all” model, and we’re still learning what works best for different use cases. That said, it is clear to us that gpt-4o is the best all-around model for agents that use actions, and the llama models seem to be the funniest on average.

Happy agent building!