Processing 2,500 lines of code (~28,000 tokens) with Llama 3.1 8B Instruct costs $0.0014 for codebase ingestion and $0.001848 for an AI-powered code review and refactoring pass.
Feed 2,500 lines of code into the prompt context for repository search, Q&A, or architecture planning.
Ingest 2,500 lines of code and generate audit findings, unit test recommendations, and refactor diffs.
Llama 3.1 8B Instruct writes 2,500 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| Llama 3.1 8B Instruct (Current) | meta | $0.0014 | $0.00035 | $0.001848 | 128,000 |
| GPT-5.6 Luna | openai | $0.0051 | $0.00051 | $0.0112 | 1,050,000 |
| GPT-5.4 mini | openai | $0.0191 | $0.001912 | $0.0421 | 256,000 |
| GPT-5.4 nano | openai | $0.0051 | $0.00051 | $0.0115 | 128,000 |
| GPT-4o mini | openai | $0.003825 | $0.001912 | $0.006885 | 128,000 |
| Claude Haiku 4.5 | anthropic | $0.028 | $0.0028 | $0.056 | 1,000,000 |
On average, code yields approximately 11.2 tokens per line in Llama 3.1 8B Instruct (tiktoken_cl100k tokenizer). Indentation, brackets, camelCase variable names, and comments slightly increase token density compared to plain English text. 2,500 lines of code produces approximately 28,000 tokens.
Sending 2,500 lines of code as context and generating a thorough code review with recommendations costs approximately $0.001848. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.000798.
Llama 3.1 8B Instruct has a context window of 128,000 tokens. 2,500 lines of code consumes 21.88% of its total available context.