A standard 100 pages document (~50,000 words / 66,650 tokens) costs $0.00 to ingest and $0.00 to generate a comprehensive executive summary using OpenRouter Free Tier (Llama 3.3).
Feed the entire 100 pages document into context to extract fields, entities, or answer queries.
Ingest 100 pages and generate a structured 500-token executive summary with key takeaways.
Translate or reformat the entire 100 pages document into an equivalent length output.
| Model | Provider | Ingestion (100 pages) | Cached Ingestion | Summary Cost | Context Limit |
|---|---|---|---|---|---|
| OpenRouter Free Tier (Llama 3.3) (Current) | openrouter | $0.00 | $0.00 | $0.00 | 64,000 |
| GPT-5.6 Luna | openai | $0.0128 | $0.00128 | $0.0134 | 1,050,000 |
| GPT-5.4 mini | openai | $0.048 | $0.0048 | $0.0503 | 256,000 |
| GPT-5.4 nano | openai | $0.0128 | $0.00128 | $0.0134 | 128,000 |
| GPT-4o mini | openai | $0.0096 | $0.0048 | $0.0099 | 128,000 |
| Claude Haiku 4.5 | anthropic | $0.066 | $0.0066 | $0.0685 | 1,000,000 |
Assuming a standard single-spaced document with ~500 words per page, a 100 pages document contains approximately 50,000 words, which translates to roughly 66,650 tokens using OpenRouter Free Tier (Llama 3.3)'s tokenizer. Dense PDF tables, legal boilerplate, and OCR scans may increase this by 20–30%.
OpenRouter Free Tier (Llama 3.3) has a context window of 64,000 tokens. A 100 pages document consumes only 104.14% of its total window, easily fitting in a single prompt without requiring chunking or vector search.
Ingesting the document and outputting a concise 500-token executive summary costs $0.00. Using 24-hour async batch API queues drops this cost to $0.00.
If your workflow repeatedly queries or chats with this same 100 pages document, prompt caching reduces subsequent turn input costs by up to 90% (to $0.00 per turn instead of $0.00).