Processing 50,000 lines of code (~560,000 tokens) with DeepSeek Coder V2.5 costs $0.0784 for codebase ingestion and $0.1098 for an AI-powered code review and refactoring pass.
Quick answer
A 50,000 lines of code codebase is estimated at 560,000 tokens for DeepSeek Coder V2.5. Ingestion costs $0.0784; a review and refactoring pass with roughly 20% output costs about $0.1098.
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 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.
DeepSeek Coder V2.5 writes 50,000 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| DeepSeek Coder V2.5 (Current) | deepseek | $0.0784 | $0.00784 | $0.1098 | 128,000 |
| GPT-5.3 Codex | openai | $0.8925 | $0.0893 | $2.321 | 256,000 |
| Codestral 2501 | mistral | $0.147 | $0.0147 | $0.2352 | 256,000 |
| Grok Build 0.1 | xai | $0.56 | $0.112 | $0.784 | 256,000 |
| Qwen 2.5 Coder 32B | qwen | $0.112 | $0.0112 | $0.1792 | 128,000 |
| GLM-5.3 (Z.ai) | zai | $0.784 | $0.1456 | $1.277 | 1,048,576 |
On average, code yields approximately 11.2 tokens per line in DeepSeek Coder V2.5 (deepseek_bpe 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 $0.1098. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.0392.
DeepSeek Coder V2.5 has a context window of 128,000 tokens. 50,000 lines of code consumes 437.50% of its total available context.