Processing 10,000 lines of code (~112,000 tokens) with OpenRouter Free Tier (Llama 3.3) costs $0.00 for codebase ingestion and $0.00 for an AI-powered code review and refactoring pass.
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.
OpenRouter Free Tier (Llama 3.3) writes 10,000 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| OpenRouter Free Tier (Llama 3.3) (Current) | openrouter | $0.00 | $0.00 | $0.00 | 64,000 |
| GPT-5.6 Luna | openai | $0.0204 | $0.00204 | $0.0449 | 1,050,000 |
| GPT-5.4 mini | openai | $0.0765 | $0.00765 | $0.1683 | 256,000 |
| GPT-5.4 nano | openai | $0.0204 | $0.00204 | $0.0459 | 128,000 |
| GPT-4o mini | openai | $0.0153 | $0.00765 | $0.0275 | 128,000 |
| Claude Haiku 4.5 | anthropic | $0.112 | $0.0112 | $0.224 | 1,000,000 |
On average, code yields approximately 11.2 tokens per line in OpenRouter Free Tier (Llama 3.3) (tiktoken_cl100k 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 $0.00. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.00.
OpenRouter Free Tier (Llama 3.3) has a context window of 64,000 tokens. 10,000 lines of code consumes 175.00% of its total available context.