AI Documentation Generation Cost: README, JSDoc, Docstrings Compared Across Claude, GPT, and Gemini
By Eric Bush · June 30, 2026 · 8 min read
The Workflow That Actually Justifies AI
Documentation is one of the most reliable wins for AI coding tools. Unlike feature implementation, where AI can introduce subtle bugs, doc generation has a clear correctness criterion: does the doc describe what the code does? Reviewers catch hallucinations quickly because the code is right there.
But not all doc generation is equal in cost. Generating JSDoc for a single function is cheap. Generating a full README for a 50K-line project is significantly more expensive than naive math suggests. Let's break it down.
Token Cost Per 1000 Lines of Code
Empirical numbers from production doc-generation projects, normalized to 1000 lines of source code documented:
| Doc Type | Input Tokens | Output Tokens | Total Per 1K LOC |
|---|---|---|---|
| Function-level JSDoc / docstrings | ~15K | ~4K | ~19K |
| Module-level summary docs | ~12K | ~2K | ~14K |
| README + getting-started guide | ~25K (file headers only) | ~3K | ~28K |
| API reference (full coverage) | ~30K | ~8K | ~38K |
| Architecture / ADR-style docs | ~40K (cross-file context) | ~5K | ~45K |
Cost in Dollars: 50K Line Project
Documenting a mid-sized 50K-line codebase across all doc types:
| Model | JSDoc Only | JSDoc + README | Full Coverage |
|---|---|---|---|
| Claude Opus 4.8 | $26 | $50 | $120 |
| GPT-5.6 Sol | $12 | $24 | $56 |
| Claude Sonnet 4.6 | $3.50 | $7 | $17 |
| Gemini 3.5 Flash | $1.40 | $2.90 | $7 |
| DeepSeek V4-Flash | $0.95 | $1.90 | $4.50 |
Quality Differences That Matter
Cost is half the story; output quality varies meaningfully across doc types:
Function-level JSDoc / docstrings: Any model from Sonnet/Flash tier and up handles this well. The task is constrained — describe parameters, return value, side effects. Even DeepSeek V4-Flash is acceptable here. Don't pay frontier prices.
README and getting-started: Quality gap widens. Frontier models produce better narrative structure, better example code, and catch missing prerequisites (Node version, env vars, install order). Spending the extra $20-30 on Opus or Sol pays off in fewer support tickets.
Architecture docs: Frontier-tier territory. The task requires cross-file synthesis ("how does the auth service interact with the rate limiter?"). Cheap models miss these connections and produce surface-level docs. Use Claude Opus 4.8 or GPT-5.6 Sol for this layer specifically.
The Maintenance Multiplier
One-shot doc generation undervalues the real cost story. Docs go stale; you regenerate. Three patterns and their costs:
1. Per-PR delta docs: CI step that updates docs only for changed files. Per-PR cost on Sonnet 4.6: $0.03-0.10. Annualized for a team shipping 200 PRs/month: $80-250/year. Cheap.
2. Quarterly full regeneration: Full doc rebuild once a quarter. For a 50K-line repo on Sonnet 4.6: $17/quarter, $68/year. Also cheap.
3. Continuous regeneration on every commit: Don't do this. It burns money for no benefit. Most commits don't change docs-worthy behavior.
Cost-Optimal Setup
For a 50K-line codebase shipping at normal pace:
Tier 1 — function/module docs: Gemini 3.5 Flash or DeepSeek V4-Flash, regenerated per-PR for changed files. Budget: $50-150/year.
Tier 2 — README and getting-started: GPT-5.6 Sol or Claude Opus 4.8, regenerated quarterly. Budget: $40-100/year.
Tier 3 — architecture docs: Claude Opus 4.8 for cross-file synthesis, regenerated only on major refactors. Budget: $30-80/year.
Total annual cost: $120-330. For a team of 5 engineers, this is well under one hour of one engineer's time. The ROI on AI-generated docs is, in practice, almost always positive.
Want to calculate exact costs for your project?
Frequently Asked Questions
What's the cheapest acceptable model for JSDoc and docstring generation?
Gemini 3.5 Flash or DeepSeek V4-Flash. Both produce accurate, well-formatted function-level documentation at a fraction of frontier prices. Quality gap vs Claude Opus is small for this task type.
Should I use the same model for README and JSDoc?
Usually not. README benefits from frontier-tier narrative quality (Claude Opus 4.8 or GPT-5.6 Sol). JSDoc is structured enough that cheap-tier models handle it without quality loss.
How much does it cost to keep docs in sync with code over a year?
Per-PR delta updates on a cheap-tier model run $80-250/year for a team shipping 200 PRs/month on a 50K-line repo. Full quarterly regeneration adds another $60-100. Both combined sit well under $500/year.
Are AI-generated architecture docs trustworthy?
Only with frontier models and human review. Cross-file synthesis is where cheap models hallucinate connections that don't exist. Claude Opus 4.8 or GPT-5.6 Sol on architecture docs, then read every word before publishing.
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