Processing 5,000 lines of code (~56,000 tokens) with NVIDIA Nemotron-4 340B costs $0.084 for codebase ingestion and $0.1176 for an AI-powered code review and refactoring pass.
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.
NVIDIA Nemotron-4 340B writes 5,000 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| NVIDIA Nemotron-4 340B (Current) | nvidia | $0.084 | $0.021 | $0.1176 | 128,000 |
| GPT-5.6 Sol | openai | $0.255 | $0.0255 | $0.561 | 1,050,000 |
| GPT-5.6 Cyber | openai | $0.6375 | $0.0638 | $1.402 | 1,050,000 |
| GPT-5.5 Standard | openai | $0.255 | $0.0255 | $0.561 | 512,000 |
| GPT-5.5 Pro | openai | $1.53 | $0.153 | $3.366 | 512,000 |
| o3-pro (Frontier Reasoning) | openai | $1.02 | $0.102 | $1.836 | 1,000,000 |
On average, code yields approximately 11.2 tokens per line in NVIDIA Nemotron-4 340B (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 $0.1176. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.0546.
NVIDIA Nemotron-4 340B has a context window of 128,000 tokens. 5,000 lines of code consumes 43.75% of its total available context.