Models & Pricing

Select the right level of intelligence for your agents from a diverse range of state-of-the-art AI models.

This guide outlines the available models, their credit costs, and how consumption is calculated in SVAHNAR.

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💎 Available Models

The following models are available for immediate use in your agent configurations.

Provider	Model Name (Config ID)	Credits Per Run
OpenAI	gpt-4o-mini	1
	gpt-4o	15
	gpt-5-nano	1
	gpt-5-mini	3
	gpt-5	15
	gpt-oss-120b	1
	gpt-oss-20b	1
Meta Llama	llama3-1-8b-instruct	1
	llama3-3-70b-instruct	2
	llama4-maverick-17b-instruct	2
Deepseek	deepseek.v3.2	3
	deepseek.r1-v1:0	7
Qwen	qwen3-32b	1
	qwen3-coder-30b-a3b	1
	qwen3-235b-a22b	4
	qwen3-vl-235b-a22b	4
	qwen3-coder-next	4

Enterprise

Need custom solutions? Enterprise customers can contact sales for access to fine-tuned models or custom deployments.

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📚 Practical Recipes

Setting the Model in Config

To use a specific model, copy the Model Name from the table above and paste it into the model parameter of your YAML configuration.

Use Case: Configuring an agent to use a cost-effective model for simple tasks.

create_agent_network:
  agent-1:
    agent_name: simple_task_agent
    LLM_config:
        params:
          # Paste the Model Name here
          model: gpt-4o-mini
    tools: []
    agent_function:
      - Reply to the user's greeting.

💡 Core Concepts

Before selecting a model, it is important to understand how SVAHNAR calculates usage.

1. What is a "Run"?

In a multi-agent network, pricing is calculated based on Runs. A Run occurs whenever an agent is triggered to perform a task or participate in a conversation.

2. How are credits consumed?

Credits are deducted strictly on a pay-per-run basis.

• If an agent uses gpt-4o-mini, 1 credit is deducted for that turn.
• If an agent uses gpt-5, 15 credits are deducted for that turn.

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In a complex workflow where multiple agents interact, the total cost is the sum of the credits required for each agent's individual participation.