USE CASE · VERIFIED 14 JUL 2026
The cheapest AI API for long-document summarization
Summarization is the most input-skewed workload shape there is: you feed in a large document and get back a few hundred words. That asymmetry changes the cost math completely compared to a balanced chat workload — the input price, not the output price, is what actually determines your bill.
Worked example: 800M input, 5M output tokens/month
A realistic shape for summarizing long documents — reports, transcripts, contracts — at real volume.
At this input-to-output ratio, the gap between the cheapest model shown and GPT-4o (the priciest one in this specific table) is nearly 17x — far wider than the roughly 6x gap you'd see on a balanced chat workload. This is the single biggest reason to actually calculate your specific token ratio instead of assuming a pricier model costs "a bit more." True flagship-tier models (Claude Opus 4.8, GPT-5.5, Claude Fable 5) would push that gap considerably further still — see the full price table for those figures.
Does summarization actually need a flagship model?
Often, no. Straightforward summarization — condensing a report into key points, extracting action items from a transcript — is exactly the kind of task budget-tier models handle well, because the skill required is compression and extraction, not deep multi-step reasoning. Reserve the mid or flagship tier for summarization that requires genuine judgment: legal document review where nuance matters, or synthesizing conflicting information across multiple sources into a coherent take.
Context window sets your ceiling, not just your cost
Gemini's 1M-token context window (both 2.5 Flash and 3 Flash) means a single call can hold an entire long report without chunking it into pieces — which matters for quality, not just convenience, since chunked summarization can lose connections between sections that only make sense read together. If your documents regularly exceed 100K tokens, check the context window before you check the price; a cheaper model that can't fit the document in one call may cost you more in workarounds than the price difference saves.
How we'd actually decide
- Straightforward summarization at volume: Gemini 2.5 Flash — cheapest, and its 1M context handles most documents in a single call.
- Summarization requiring real judgment (legal, financial, conflicting sources): Claude Sonnet 5 — worth the roughly 13x cost jump for tasks where getting it wrong is expensive.
- Documents that regularly exceed 1M tokens: Gemini 3.1 Pro — the only tracked model with headroom to spare at 2M tokens.
Worked example uses standard (non-batch, non-cached) list pricing verified 14 July 2026. Use the calculator with your own document volume and length for an exact estimate.