Processing 5,000 lines of code (~49,000 tokens) with Mistral Large 3 costs $0.0245 for codebase ingestion and $0.0392 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.
Mistral Large 3 writes 5,000 lines of code from scratch based on product specifications.
| Model | Provider | Code Ingestion | Cached Ingestion | Code Review Cost | Context Limit |
|---|---|---|---|---|---|
| Mistral Large 3 (Current) | mistral | $0.0245 | $0.00245 | $0.0392 | 1,000,000 |
| 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 9.8 tokens per line in Mistral Large 3 (mistral_bpe tokenizer). Indentation, brackets, camelCase variable names, and comments slightly increase token density compared to plain English text. 5,000 lines of code produces approximately 49,000 tokens.
Sending 5,000 lines of code as context and generating a thorough code review with recommendations costs approximately $0.0392. Utilizing prompt caching on repeat turns or static repository definitions drops this to $0.0172.
Mistral Large 3 has a context window of 1,000,000 tokens. 5,000 lines of code consumes 4.90% of its total available context.