Processing 10,000 lines of code (~102,000 tokens) with GPT-5.3 Codex costs $0.1785 for codebase ingestion and $0.4641 for an AI-powered code review and refactoring pass.
Feed 10,000 lines of code into the prompt context for repository search, Q&A, or architecture planning.
Ingest 10,000 lines of code and generate audit findings, unit test recommendations, and refactor diffs.
GPT-5.3 Codex writes 10,000 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| GPT-5.3 Codex (Current) | openai | $0.1785 | $0.0178 | $0.4641 | 256,000 |
| DeepSeek Coder V2.5 | deepseek | $0.0157 | $0.001568 | $0.022 | 128,000 |
| Codestral 2501 | mistral | $0.0294 | $0.00294 | $0.047 | 256,000 |
| Grok Build 0.1 | xai | $0.112 | $0.0224 | $0.1568 | 256,000 |
| Qwen 2.5 Coder 32B | qwen | $0.0224 | $0.00224 | $0.0358 | 128,000 |
| DeepInfra — Qwen 2.5 Coder 32B | deepinfra | $0.00896 | $0.00224 | $0.0143 | 128,000 |
On average, code yields approximately 10.2 tokens per line in GPT-5.3 Codex (o200k_base tokenizer). Indentation, brackets, camelCase variable names, and comments slightly increase token density compared to plain English text. 10,000 lines of code produces approximately 102,000 tokens.
Sending 10,000 lines of code as context and generating a thorough code review with recommendations costs approximately $0.4641. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.3035.
GPT-5.3 Codex has a context window of 256,000 tokens. 10,000 lines of code consumes 39.84% of its total available context.