Processing 5,000 lines of code (~56,000 tokens) with Llama 3.1 8B Instruct costs $0.0028 for codebase ingestion and $0.003696 for an AI-powered code review and refactoring pass.
Quick answer
A 5,000 lines of code codebase is estimated at 56,000 tokens for Llama 3.1 8B Instruct. Ingestion costs $0.0028; a review and refactoring pass with roughly 20% output costs about $0.003696.
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.
Llama 3.1 8B Instruct writes 5,000 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 | $0.0028 | $0.0007 | $0.003696 | 128,000 |
| GPT-5.6 Luna | openai | $0.0102 | $0.00102 | $0.0224 | 1,050,000 |
| GPT-5.4 mini | openai | $0.0383 | $0.003825 | $0.0842 | 256,000 |
| GPT-5.4 nano | openai | $0.0102 | $0.00102 | $0.023 | 128,000 |
| GPT-4o mini | openai | $0.00765 | $0.003825 | $0.0138 | 128,000 |
| Claude Haiku 4.5 | anthropic | $0.056 | $0.0056 | $0.112 | 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. 5,000 lines of code produces approximately 56,000 tokens.
Sending 5,000 lines of code as context and generating a thorough code review with recommendations costs approximately $0.003696. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.001596.
Llama 3.1 8B Instruct has a context window of 128,000 tokens. 5,000 lines of code consumes 43.75% of its total available context.