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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Don’t use outdated models.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.

Supported Providers

ProviderAPI Key LocationModels
Anthropicconsole.anthropic.comClaude Opus 4.6, Sonnet 4.6, Haiku 4.5
OpenAIplatform.openai.comGPT-5.4, GPT-5.4 Mini, GPT-5.4 Nano
Googleaistudio.google.devGemini 3.1 Pro, Gemini 3 Flash
xAIconsole.x.aiGrok 4-1
Azure OpenAIAzure PortalAny deployed model
Add your API key in Control Hub > Providers to unlock that provider’s models across all your agents. These are the three models you should be choosing between for most agents:

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.
SpecValue
Input$3.00 / 1M tokens
Output$15.00 / 1M tokens
Context1M tokens
Max Output64K tokens
StrengthsInstruction following, tool use, structured output, long documents
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.

Claude Opus 4.6 — Maximum Capability

The most capable model for tasks requiring deep reasoning, complex multi-step planning, or handling ambiguous instructions.
SpecValue
Input$5.00 / 1M tokens
Output$25.00 / 1M tokens
Context1M tokens
Max Output128K tokens
StrengthsComplex reasoning, nuanced judgment, long-form generation, ambiguous tasks
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.

GPT-5.4 — Strong Alternative

OpenAI’s flagship. Competitive with Claude Opus on overall benchmarks, with slightly different strengths.
SpecValue
Input$2.50 / 1M tokens
Output$15.00 / 1M tokens
Context1M tokens
Max Output128K tokens
StrengthsBroad knowledge, web search tool, image generation, code interpretation
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.

Budget-Friendly Options

For high-volume or cost-sensitive workloads:
ModelInputOutputBest For
GPT-5.4 Mini$0.75 / 1M$4.50 / 1MCapable subagents, classification, extraction
GPT-5.4 Nano$0.20 / 1M$1.25 / 1MHigh-volume routing, simple classification, triage
Claude Haiku 4.5$1.00 / 1M$5.00 / 1MFast responses, simple Q&A, scheduled monitoring tasks
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.

Choosing by Use Case

Agent TypeRecommended ModelWhy
CRM data entry / updatesSonnet 4.6Reliable tool use, fast, cost-effective
Document analysis & extractionSonnet 4.6Strong structured output, large context
Legal / compliance reviewOpus 4.6Nuanced judgment, handles ambiguity
Financial analysisOpus 4.6Complex reasoning, accuracy matters
Customer-facing chatbotSonnet 4.6Fast responses, good instruction following
Scheduled monitoring tasksHaiku 4.5Runs frequently, cost matters, simple logic
Research agentsOpus 4.6 or GPT-5.4Deep reasoning + web search (GPT-5.4)
Multi-agent orchestratorSonnet 4.6Fast coordination, reliable tool dispatch
Subagent / workerGPT-5.4 Mini or Haiku 4.5Cost-efficient for delegated subtasks
Data classification / triageGPT-5.4 NanoUltra-cheap, high-volume

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.

Provider Tools

Some providers include built-in tools that extend your agent’s capabilities beyond Aster’s standard tool library:
ProviderToolDescription
OpenAIWeb SearchSearch the web for current information
OpenAICode InterpreterWrite and execute Python code in a sandbox
OpenAIImage GenerationGenerate images from text prompts
GoogleGoogle SearchGround responses with real-time search results
GoogleCode ExecutionGenerate and run Python code
xAIX SearchSearch X (Twitter) for posts and discussions
xAIWeb SearchSearch the web for current information
These tools appear automatically when you select a model from the corresponding provider. They can be enabled alongside Aster’s standard tools.