Processing 10,000 lines of code (~112,000 tokens) with GPT-3.5 Turbo costs $0.056 for codebase ingestion and $0.0896 for an AI-powered code review and refactoring pass.
Quick answer
A 10,000 lines of code codebase is estimated at 112,000 tokens for GPT-3.5 Turbo. Ingestion costs $0.056; a review and refactoring pass with roughly 20% output costs about $0.0896.
Method & trust
Code is estimated at a tokenizer-specific tokens-per-line ratio, then priced separately for repository context and generated review output. Comments, minified files, tests, and repeated context can materially change the bill.
Feed 10,000 lines of code into the prompt context for repository search, Q&A, or architecture planning.
Ingest 10,000 lines of code and generate audit findings, unit test recommendations, and refactor diffs.
GPT-3.5 Turbo writes 10,000 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| GPT-3.5 Turbo (Current) | openai | $0.056 | $0.014 | $0.0896 | 16,385 |
| GPT-4 Turbo | openai | $1.12 | $0.56 | $1.792 | 128,000 |
| GLM-4-32B-0414-128K (Z.ai) | zai | $0.0112 | $0.0028 | $0.0134 | 128,000 |
On average, code yields approximately 11.2 tokens per line in GPT-3.5 Turbo (cl100k_base tokenizer). Indentation, brackets, camelCase variable names, and comments slightly increase token density compared to plain English text. 10,000 lines of code produces approximately 112,000 tokens.
Sending 10,000 lines of code as context and generating a thorough code review with recommendations costs approximately $0.0896. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.0476.
GPT-3.5 Turbo has a context window of 16,385 tokens. 10,000 lines of code consumes 683.55% of its total available context.