Processing 100 lines of code (~1,020 tokens) with GPT-5.6 Luna costs $0.000204 for codebase ingestion and $0.000449 for an AI-powered code review and refactoring pass.
Feed 100 lines of code into the prompt context for repository search, Q&A, or architecture planning.
Ingest 100 lines of code and generate audit findings, unit test recommendations, and refactor diffs.
GPT-5.6 Luna writes 100 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| GPT-5.6 Luna (Current) | openai | $0.000204 | $0.000020 | $0.000449 | 1,050,000 |
| GPT-5.4 mini | openai | $0.000765 | $0.000077 | $0.001683 | 256,000 |
| GPT-5.4 nano | openai | $0.000204 | $0.000020 | $0.000459 | 128,000 |
| GPT-4o mini | openai | $0.000153 | $0.000077 | $0.000275 | 128,000 |
| Claude Haiku 4.5 | anthropic | $0.00112 | $0.000112 | $0.00224 | 1,000,000 |
| Claude 3.5 Haiku | anthropic | $0.000896 | $0.000090 | $0.001792 | 200,000 |
On average, code yields approximately 10.2 tokens per line in GPT-5.6 Luna (o200k_base tokenizer). Indentation, brackets, camelCase variable names, and comments slightly increase token density compared to plain English text. 100 lines of code produces approximately 1,020 tokens.
Sending 100 lines of code as context and generating a thorough code review with recommendations costs approximately $0.000449. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.000265.
GPT-5.6 Luna has a context window of 1,050,000 tokens. 100 lines of code consumes 0.10% of its total available context.