Processing 2,500 lines of code (~28,000 tokens) with DeepSeek R1 (Reasoner) costs $0.0154 for codebase ingestion and $0.0277 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.
DeepSeek R1 (Reasoner) writes 2,500 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| DeepSeek R1 (Reasoner) (Current) | deepseek | $0.0154 | $0.00392 | $0.0277 | 64,000 |
| GPT-5.6 Terra | openai | $0.051 | $0.0051 | $0.1122 | 1,050,000 |
| GPT-5.4 Workhorse | openai | $0.0638 | $0.006375 | $0.1403 | 256,000 |
| o3-mini | openai | $0.0281 | $0.014 | $0.0505 | 200,000 |
| o4-mini | openai | $0.0281 | $0.007013 | $0.0505 | 256,000 |
| o1-mini | openai | $0.0281 | $0.014 | $0.0505 | 128,000 |
On average, code yields approximately 11.2 tokens per line in DeepSeek R1 (Reasoner) (deepseek_bpe 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 $0.0277. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.0162.
DeepSeek R1 (Reasoner) has a context window of 64,000 tokens. 2,500 lines of code consumes 43.75% of its total available context.