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A model serves as an agent’s cognitive engine, providing the reasoning capabilities needed to understand tasks, determine the best course of action, and generate responses. Every agent requires a model to function.

Model types

SeekrFlow supports two types of models for agents:

Base models

Base models are pre-trained models available on the SeekrFlow platform. These models provide general-purpose reasoning capabilities and can handle a wide range of tasks without additional training. SeekrFlow supports various base models from leading providers:

Meta Llama models

Qwen models

Mistral AI models

DeepSeek models

Google Gemma models

Other models

For the complete list of available base models with detailed specifications, see the Models API reference.

Fine-tuned models

Fine-tuned models are custom-trained models adapted to specific domains or use cases. These models are created through SeekrFlow’s fine-tuning component, which embeds specialized knowledge and behaviors directly into model parameters.

Selecting a model

When configuring an agent, you specify which model to use. Consider these factors when selecting a model:
  • Task complexity – More complex reasoning tasks may benefit from larger or specialized models.
  • Response requirements – Balance between speed and accuracy based on your use case.
  • Domain specificity – Fine-tuned models perform better for specialized domains with unique terminology or requirements.
  • Cost and performance – Larger models provide enhanced capabilities but with higher computational costs.

Model configuration

Models are specified during agent creation and can be updated by modifying the agent configuration. The model works in conjunction with other agent components like instructions and tools to determine overall agent behavior.
Last modified on July 2, 2026