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Overview

Aster Agents supports bring-your-own-API-key across multiple providers. You connect your own API keys in Control Hub > Providers, then select a model when building each agent. This gives you full control over cost, performance, and provider choice.
Don’t use outdated models. Models like GPT-4o, Claude 3.5 Sonnet, or GPT-4.1 are previous-generation and significantly underperform current models on agentic tasks. Always use the latest models listed below.

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Supported Providers

Add your API key in Control Hub > Providers to unlock that provider’s models across all your agents.

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Model Identifiers

When configuring a model — in the UI, the API, or via the manage_agents tool — the platform expects the provider:model-id format, not the display name. "claude-sonnet-4-6" will not work; "anthropic:claude-sonnet-4-6" will. For the complete list including legacy and embedding models, see Control Hub > Models in the dashboard. These are the three models you should be choosing between for most agents.

Start with Sonnet 5

The latest and greatest at mid-tier pricing — near-Opus quality on tool use, document analysis, structured output, and customer-facing work, but cheaper than Opus. The right default for most agents.

Upgrade to Opus 5 for judgment calls

Reach for Opus when your agent regularly hits ambiguity, complex reasoning, or tasks where subtle errors have real consequences.

Choose GPT-5.4 for OpenAI's built-in tools

Pick GPT-5.4 when you need web_search, code_interpreter, or image_generation, or your team is already invested in the OpenAI ecosystem.

Claude Sonnet 5

Best all-around. The default choice for most agents. Near-flagship intelligence at mid-tier pricing with the fastest output speed of any frontier model.

Claude Opus 5

Maximum capability. The most capable model for tasks requiring deep reasoning, complex multi-step planning, or handling ambiguous instructions.

GPT-5.4

Strong alternative. OpenAI’s flagship. Competitive with Claude Opus on overall benchmarks, with slightly different strengths.
Best for: General-purpose agents, CRM workflows, document analysis, data extraction, customer-facing agents, scheduled tasks, multi-tool orchestration.Why Sonnet over Opus? Sonnet lands within a couple of points of Opus on coding and agentic benchmarks while being significantly faster and 40% cheaper. For most agent tasks — querying databases, filling out forms, searching knowledge bases, writing emails — the difference is imperceptible.
Best for: Legal document analysis, financial modeling, research agents, complex multi-agent workflows, agents that need to handle edge cases gracefully, tasks where accuracy matters more than cost.When to choose Opus: When your agent regularly encounters situations that require judgment calls — interpreting vague requirements, handling conflicting information, or producing output where subtle errors have real consequences.
Best for: Agents that need OpenAI’s built-in tools (web search, code interpreter, image generation), teams already invested in the OpenAI ecosystem, general-purpose agents where input cost sensitivity matters.OpenAI-exclusive tools: GPT-5.4 unlocks web_search, code_interpreter, and image_generation as provider tools — these aren’t available with other providers.

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Budget-Friendly Options

For high-volume or cost-sensitive workloads:
These models are excellent for multi-agent workflows where a cheaper model handles routine subtasks (classification, data formatting, simple lookups) while a flagship model handles the complex reasoning.

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Choosing by Use Case

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Cost Optimization Tips

  1. Start with Sonnet 5 — it handles 90%+ of agent tasks well. Only upgrade to Opus if you see quality issues on specific tasks.
  2. Use cheaper models for subagents — in multi-agent workflows, the orchestrator can run on Sonnet while worker agents run on Haiku or GPT-5.4 Mini.
  3. Prompt caching saves money — both Anthropic (90% off cached input) and OpenAI (50% off cached input) automatically cache repeated context. Agents with large system prompts or knowledge base content benefit significantly.
  4. Keep system prompts focused — longer prompts cost more on every message. A concise, well-structured prompt outperforms a verbose one and costs less.

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Provider Tools

Some providers include built-in tools that extend your agent’s capabilities beyond Aster’s standard tool library: These tools appear automatically when you select a model from the corresponding provider. They can be enabled alongside Aster’s standard tools.