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OpenRouter LLM Intelligence & Model Pricing

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Live intelligence on 440+ LLMs on OpenRouter. Normalized per-1M token pricing, context windows, free models, multi-modal specs, and market analysis.

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OpenRouter LLM Intelligence, Pricing Matrix & Benchmark Analytics

OpenRouter LLM Intelligence is an enterprise-grade AI model pricing matrix, context leaderboard, and capability scraper designed by Prime Sieve.

It pulls live real-time intelligence on 440+ LLMs & Multi-modal models hosted on OpenRouter — including DeepSeek, Anthropic Claude, OpenAI GPT-4.5/o3, Google Gemini 2.0/Flash, Meta Llama 3.3, Mistral, and open-source fine-tunes.

⚡ What Data You Get

For every single model, this Actor extracts and normalizes:

Identifier & Creator: anthropic/claude-3.7-sonnet, deepseek/deepseek-r1, openai/gpt-4.5-preview, etc.
Normalized Pricing: Exact USD cost per 1 Million Input Tokens and 1 Million Output Tokens (no scientific notation math required).
Context Window: Total token capacity (from 8K up to 2M tokens).
Modalities: text->text, text+image->text, audio, and embeddings.
Free Tier Detection: Flags :free and $0/1M token models for cost-free development.
Market Intelligence Summary: Automated breakdown of median token costs across the AI industry, top providers by model count, and top largest context window leaders.

💡 Use Cases

AI Cost Optimization: Continuously monitor price drops and token arbitrage across competitive providers.
Dynamic LLM Routers: Feed live price & context specs into custom agent routers and fallback systems.
AI Industry Research: Benchmark model pricing curves and track the rapid commoditization of frontier tokens.
Developer Tooling: Build auto-updating model pickers and cost estimation calculators for SaaS apps.

⚙️ Input Parameters

Parameter	Type	Default	Description
`searchQuery`	String	`""`	Filter by keyword (e.g. `deepseek`, `claude`, `reasoning`, `vision`)
`providerFilter`	String	`"all"`	Filter by creator slug (e.g. `anthropic`, `openai`, `deepseek`, `meta-llama`)
`freeOnly`	Boolean	`false`	Only return $0 / free tier models
`filterModality`	String	`"all"`	Filter by modality (`text->text`, `text+image->text`)
`minContextLength`	Integer	`0`	Minimum token context window (e.g. `128000`)
`maxPromptPricePerMillion`	Number	`0`	Max input price ($ / 1M tokens)
`sortBy`	String	`"promptPriceAsc"`	Sort by price, context length, or name
`includeMarketSummary`	Boolean	`true`	Include an aggregate industry summary item
`maxResults`	Integer	`500`	Max records to output (0 for unlimited)

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