GPT-5.2 Codex vs Mistral Codestral: developer-focused coding costs
Mistral Codestral is more economical, offering cheaper base inputs and output rates. Use GPT-5.2 Codex if your code pipeline is deeply integrated into OpenAI's ecosystem.
Developer-focused auto-complete and refactoring endpoints.
Dedicated coding endpoints offer tuned performance for auto-complete and refactoring. GPT-5.2 Codex and Mistral Codestral represent two leading specialized developer APIs.
By TechCompare · Updated
Cost Comparison
Based on 100,000 input tokens (50% cached), 5,000 output tokens, and 100 requests.
Side-by-side specs
| Spec | GPT-5.2 Codex | Mistral Codestral |
|---|---|---|
| Input Cost (per M) | $1.75 | $1.50 (better on this spec) |
| Output Cost (per M) | $14.00 | $7.50 (better on this spec) |
| Cached Input (per M) | $0.175 | $0.15 (better on this spec) |
| Batch Discount | 0% | 50% (better on this spec) |
How they differ
GPT-5.2 Codex costs $1.75 per million input tokens and $14.00 per million output tokens, with a 90% caching discount. Mistral Codestral is priced at $1.50 per million input tokens and $7.50 per million output tokens, also with a 90% caching discount.
Verdict
Codestral wins every row: $1.50/M input against $1.75, $7.50/M output against $14.00 (about 1.9x), and $0.15/M cached input against $0.175. It also adds a 50% batch discount where Codex offers none, dropping batch output to $3.75/M versus Codex's live $14.00/M. The 90% cache discount is equal on both, so the absolute dollar gap holds at the cached tier. Run the integration-cost math before paying Codex's premium for OpenAI-stack lock-in.
Which should you pick?
Choose GPT-5.2 Codex
OpenAI-standard completions pipelines and legacy auto-complete structures.
Choose Mistral Codestral
Economical multi-lingual code completion, inline refactoring, and general script generation.