How to use Financial Document Token Estimator
Paste a 10-K, 10-Q, 8-K, or earnings transcript. The page reports token count and one-pass extraction cost across ten frontier LLMs, with cache-hit toggle so you can see real-world economics, not list price.
What It Does
Use the calculator with intent
Paste a 10-K, 10-Q, 8-K, or earnings transcript. The page reports token count and one-pass extraction cost across ten frontier LLMs, with cache-hit toggle so you can see real-world economics, not list price.
Engineers building filing-analysis pipelines who need to size the model bill before committing the architecture to one provider.
Interpreting Results
Token count is the underlying cost driver. Toggle cache-hit on for realistic recurring-extraction economics. Per-document cost x docs-per-month gives you the workload bill.
Input Steps
Field by field
- 1
Pick or paste
Pick an archetype (10-K, 10-Q, 8-K, or earnings call) for a representative estimate, or paste the actual document text (up to about 50,000 characters).
- 2
Read the estimate
Read the token estimate. Pasted text is counted exactly (characters divided by the model's tokenizer ratio); archetypes use a representative mid-range count (the 10-K preset is around 18,000 tokens).
- 3
Check the Fits column
Check the Fits column — it flags, per model, whether the document overflows that model's context window (windows range from about 200K to 2M tokens). Documents that don't fit need chunking; see the SEC Filing Chunk Optimizer.
- 4
Read cost
Read the one-pass extraction cost across all ten models, and toggle the cache-hit rate to see recurring-pipeline economics.
- 5
Multiply
Multiply per-document cost by your monthly document volume to size the bill. For batch optimization across models, pair with the Token Cost Optimizer.
Common Scenarios
Use realistic starting points
10-K archive analysis
Doc type
10-K
Volume
500 docs/quarter
The tool's 10-K archetype estimates around 18,000 tokens for a representative mid-size filing; large-cap filings with full exhibits can exceed 40K. Sonnet is the typical sweet spot — Opus rarely justifies the cost step on filing analysis.
Earnings-day batch
Doc type
Earnings transcript
Volume
200 docs/day
Cache-hit toggle changes the bill dramatically — recurring extraction of the same boilerplate sections benefits most.
Try These Tools
Run the numbers next
SEC Filing Chunk Optimizer
Pick a filing archetype, tune chunk size and overlap, and see chunk count, embedding cost, and structural-boundary warnings across three chunking strategies.
Earnings-Call Summarization Cost Calculator
LLM cost per stock per quarter to summarize earnings transcripts across Sonnet, Opus, GPT-5.5, Gemini 2.5 Pro/Flash. Cache-hit-rate aware. Snapshot pricing.
Token-Cost Optimizer
Compute the dollar cost of a trading research loop across Claude, GPT, and Gemini. Prompt length × model × retry × call volume → cost per idea and per.
FAQ
Questions people ask next
The short answers readers usually want after the first pass.
Related Content