Specialized generative coding and fill-in-the-middle model fluent in 80+ programming languages
codestral-2501| Scenario | Input Tokens | Output Tokens | Uncached Cost | With Prompt Caching |
|---|---|---|---|---|
| Short Chat Query | 1,000 | 500 | $0.00050 | $0.00036 |
| Document Summarization | 10,000 | 2,000 | $0.00320 | $0.00180 |
| Codebase & Context Analysis | 100,000 | 20,000 | $0.0320 | $0.0180 |
| Batch Corpus Processing | 1,000,000 | 100,000 | $0.2600 | $0.1200 |
Ideal for production workloads demanding flagship capabilities, deep context depth (256k tokens), and reliability from Mistral AI. Excellent when predictable tokenomics and prompt caching support are paramount.
If your use-case requires sub-second streaming latency or ultra-high frequency classification at micro-cent pricing, consider lighter budget options such as Gemini Flash-Lite or Claude Haiku. For deep formal logic, consider dedicated reasoning models like o3.
For Codestral 2501, 1 million input tokens costs $0.20, while 1 million output tokens costs $0.60. If using prompt caching, repetitive input prefixes are discounted to $0.06 per million.
Codestral 2501 features a maximum context window of 256,000 tokens (~192,000 words), with a maximum output limit of 8,192 tokens per completion.
Codestral 2501 utilizes the Mistral Tekken BPE (~131k vocabulary). Token counting on TokenMath runs client-side to ensure maximum privacy.
Yes. Codestral 2501 supports prompt caching with a cached input rate of $0.06/1M (saving up to 70% on repeated input context).