Processing 1,000 lines of code (~11,200 tokens) with Gemma 2 9B Instruct costs $0.00224 for codebase ingestion and $0.002688 for an AI-powered code review and refactoring pass.
Feed 1,000 lines of code into the prompt context for repository search, Q&A, or architecture planning.
Ingest 1,000 lines of code and generate audit findings, unit test recommendations, and refactor diffs.
Gemma 2 9B Instruct writes 1,000 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| Gemma 2 9B Instruct (Current) | $0.00224 | $0.00056 | $0.002688 | 8,192 | |
| GPT-5.6 Luna | openai | $0.00204 | $0.000204 | $0.004488 | 1,050,000 |
| GPT-5.4 mini | openai | $0.00765 | $0.000765 | $0.0168 | 256,000 |
| GPT-5.4 nano | openai | $0.00204 | $0.000204 | $0.00459 | 128,000 |
| GPT-4o mini | openai | $0.00153 | $0.000765 | $0.002754 | 128,000 |
| Claude Haiku 4.5 | anthropic | $0.0112 | $0.00112 | $0.0224 | 1,000,000 |
On average, code yields approximately 11.2 tokens per line in Gemma 2 9B Instruct (sentencepiece tokenizer). Indentation, brackets, camelCase variable names, and comments slightly increase token density compared to plain English text. 1,000 lines of code produces approximately 11,200 tokens.
Sending 1,000 lines of code as context and generating a thorough code review with recommendations costs approximately $0.002688. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.001008.
Gemma 2 9B Instruct has a context window of 8,192 tokens. 1,000 lines of code consumes 136.72% of its total available context.