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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Don’t use outdated models.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 > Providers 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 4.8 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 4.6

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 4.6

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 4.6 scores within 1-2% of Opus 4.6 on coding and agentic benchmarks (79.6% vs 80.8% on SWE-bench) 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 4.6 — 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.