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LLM Component Database

This page serves as a component registry for Large Language Models. When designing your application “builds,” use this data to select models based on context requirements, cost limits, and search capabilities.


Model Name Provider Context Window Input Cost (per 1M) Output Cost (per 1M) Core Strengths (Stat Modifiers)
Gemini 2.5 Pro Google 2,000,000 $1.25 $5.00 Multi-modal reasoning, large file ingestion, long context RAG
Gemini 2.5 Flash Google 1,000,000 $0.075 $0.30 Speed, high rate-limits, lightweight agent tasks, cost efficiency
Claude 3.5 Sonnet Anthropic 200,000 $3.00 $15.00 Code generation, complex agent logic, structured JSON output
GPT-4o OpenAI 128,000 $2.50 $10.00 High general reasoning, conversational speech, fast API response
Llama 3.3 70B Meta (Open) 128,000 Self-Hosted Self-Hosted Local privacy, fine-tuning potential, high reasoning output

When selecting a model, pay attention to the passive capabilities they unlock:

  • Unlocked by: Gemini series.
  • Effect: Allows the model to search the web in real-time to verify facts, reducing hallucinations to near-zero for factual queries.
  • Unlocked by: Claude 3.5 Sonnet, GPT-4o.
  • Effect: High accuracy in parsing tool schemas and calling external APIs sequentially in agent loops.
  • Unlocked by: Most frontier models.
  • Effect: Strong adherence to system prompts and constraints under adversarial user inputs.