Processing 5,000 lines of code (~51,000 tokens) with GPT-5.6 Terra Pro (OpenRouter) costs $0.102 for codebase ingestion and $0.2244 for an AI-powered code review and refactoring pass.
Quick answer
A 5,000 lines of code codebase is estimated at 51,000 tokens for GPT-5.6 Terra Pro (OpenRouter). Ingestion costs $0.102; a review and refactoring pass with roughly 20% output costs about $0.2244.
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 5,000 lines of code into the prompt context for repository search, Q&A, or architecture planning.
Ingest 5,000 lines of code and generate audit findings, unit test recommendations, and refactor diffs.
GPT-5.6 Terra Pro (OpenRouter) writes 5,000 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| GPT-5.6 Terra Pro (OpenRouter) (Current) | openai | $0.102 | $0.0102 | $0.2244 | 1,050,000 |
| GPT-5.6 Sol | openai | $0.255 | $0.0255 | $0.561 | 1,050,000 |
| GPT-5.6 Cyber | openai | $0.6375 | $0.0638 | $1.402 | 1,050,000 |
| GPT-5.5 Standard | openai | $0.255 | $0.0255 | $0.561 | 512,000 |
| GPT-5.5 Pro | openai | $1.53 | $0.153 | $3.366 | 512,000 |
| o3-pro (Frontier Reasoning) | openai | $1.02 | $0.102 | $1.836 | 1,000,000 |
On average, code yields approximately 10.2 tokens per line in GPT-5.6 Terra Pro (OpenRouter) (o200k_base tokenizer). Indentation, brackets, camelCase variable names, and comments slightly increase token density compared to plain English text. 5,000 lines of code produces approximately 51,000 tokens.
Sending 5,000 lines of code as context and generating a thorough code review with recommendations costs approximately $0.2244. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.1326.
GPT-5.6 Terra Pro (OpenRouter) has a context window of 1,050,000 tokens. 5,000 lines of code consumes 4.86% of its total available context.