Processing 100 lines of code (~1,120 tokens) with DeepSeek R1 (Reasoner) costs $0.000616 for codebase ingestion and $0.001107 for an AI-powered code review and refactoring pass.
Feed 100 lines of code into the prompt context for repository search, Q&A, or architecture planning.
Ingest 100 lines of code and generate audit findings, unit test recommendations, and refactor diffs.
DeepSeek R1 (Reasoner) writes 100 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 | $0.000616 | $0.000157 | $0.001107 | 64,000 |
| GPT-5.6 Terra | openai | $0.00204 | $0.000204 | $0.004488 | 1,050,000 |
| GPT-5.4 Workhorse | openai | $0.00255 | $0.000255 | $0.00561 | 256,000 |
| o3-mini | openai | $0.001122 | $0.000561 | $0.00202 | 200,000 |
| o4-mini | openai | $0.001122 | $0.000281 | $0.00202 | 256,000 |
| o1-mini | openai | $0.001122 | $0.000561 | $0.00202 | 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. 100 lines of code produces approximately 1,120 tokens.
Sending 100 lines of code as context and generating a thorough code review with recommendations costs approximately $0.001107. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.000647.
DeepSeek R1 (Reasoner) has a context window of 64,000 tokens. 100 lines of code consumes 1.75% of its total available context.