Processing 50,000 lines of code (~560,000 tokens) with NVIDIA Llama 3.1 Nemotron 70B costs $0.196 for codebase ingestion and $0.2744 for an AI-powered code review and refactoring pass.
Feed 50,000 lines of code into the prompt context for repository search, Q&A, or architecture planning.
Ingest 50,000 lines of code and generate audit findings, unit test recommendations, and refactor diffs.
NVIDIA Llama 3.1 Nemotron 70B writes 50,000 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| NVIDIA Llama 3.1 Nemotron 70B (Current) | nvidia | $0.196 | $0.049 | $0.2744 | 128,000 |
| GPT-5.6 Terra | openai | $1.02 | $0.102 | $2.244 | 1,050,000 |
| GPT-5.4 Workhorse | openai | $1.275 | $0.1275 | $2.805 | 256,000 |
| o3-mini | openai | $0.561 | $0.2805 | $1.01 | 200,000 |
| o4-mini | openai | $0.561 | $0.1403 | $1.01 | 256,000 |
| o1-mini | openai | $0.561 | $0.2805 | $1.01 | 128,000 |
On average, code yields approximately 11.2 tokens per line in NVIDIA Llama 3.1 Nemotron 70B (tiktoken_cl100k tokenizer). Indentation, brackets, camelCase variable names, and comments slightly increase token density compared to plain English text. 50,000 lines of code produces approximately 560,000 tokens.
Sending 50,000 lines of code as context and generating a thorough code review with recommendations costs approximately $0.2744. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.1274.
NVIDIA Llama 3.1 Nemotron 70B has a context window of 128,000 tokens. 50,000 lines of code consumes 437.50% of its total available context.