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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 large language models (LLMs) 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

Model	Size	Best for
Llama 3.1 8B Instruct	8B	Instruction-following, general assistant tasks
Llama 3.1 70B Instruct	70B	Complex reasoning, high-accuracy tasks
Llama 3.3 70B Instruct	70B	Latest generation complex reasoning
Llama 3.2 1B/3B Instruct	1-3B	Lightweight tasks, resource-constrained environments
Llama 3.2 90B Vision Instruct	90B	Multimodal image reasoning and visual Q&A
Llama 4 Scout 17B-16E Instruct	109B (17B active)	Next-generation multimodal understanding

Qwen models

Model	Size	Best for
Qwen 2.5 3B Instruct	3B	Multilingual instruction-following
Qwen 3 8B/32B FP8	8-32B	Efficient multilingual reasoning
Qwen 2 72B	72B	Advanced natural language tasks
Qwen 2.5 VL 32B Instruct	32B	Vision and language understanding

Mistral AI models

Model	Size	Best for
Mistral 7B Instruct v0.2/v0.3	7B	Fast responses, chat applications
Mistral Small 24B Instruct	24B	Low-latency multilingual conversations
Mamba Codestral 7B	7B	Code generation and programming tasks

DeepSeek models

Model	Size	Best for
DeepSeek R1 Distill Qwen 7B	7B	Reasoning-focused conversational tasks
DeepSeek R1 Distill Qwen 32B	32B	Advanced reasoning at scale

Google Gemma models

Model	Size	Best for
Gemma 2B	2B	Lightweight general tasks
Gemma 2 9B	9B	Balanced performance and efficiency
Gemma 3 27B IT	27B	Multilingual, multimodal capabilities

Other models

Model	Size	Best for
Microsoft Phi-3 Mini 4k Instruct	3.8B	On-device and resource-constrained environments
TinyLlama 1.1B Chat	1.1B	Ultra-lightweight chat applications
OpenAI GPT-OSS 20B/120B	20-120B	Reasoning and agentic tasks

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Note
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.