Mistral flagship reasoning and coding model with aggressive 2026 pricing ($0.50/M in) Need a token count first? Use the Mistral token counter.
mistral-large-2512| Scenario | Input Tokens | Output Tokens | Uncached Cost | With Prompt Caching |
|---|---|---|---|---|
| Short Chat Query | 1,000 | 500 | $0.00125 | $0.00080 |
| Document Summarization | 10,000 | 2,000 | $0.00800 | $0.00350 |
| Codebase & Context Analysis | 100,000 | 20,000 | $0.0800 | $0.0350 |
| Batch Corpus Processing | 1,000,000 | 100,000 | $0.6500 | $0.2000 |
Tier 1 (free tier) reference limits — your account's actual quota may be higher.
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 Mistral Large 3, 1 million input tokens costs $0.50, while 1 million output tokens costs $1.50. If using prompt caching, repetitive input prefixes are discounted to $0.05 per million.
Mistral Large 3 features a maximum context window of 262,144 tokens (~196,608 words), with a maximum output limit of 16,384 tokens per completion.
Mistral Large 3 utilizes the Mistral Tekken Tokenizer (131k vocabulary). Token counting on TokenMath runs client-side to ensure maximum privacy.
Yes. Mistral Large 3 supports prompt caching with a cached input rate of $0.05/1M (saving up to 90% on repeated input context).