Mistral Small 3.1
MistralMistral Small 3.1 by Mistral costs $0.2/M input, $0.6/M output with 128K context window. Updated February 2026. Compare with GPT-5, Claude, Gemini & 40+ models.
Input Price
$0.20
per 1M tokens
Output Price
$0.60
per 1M tokens
Context Window
128K
tokens
Specifications
| Provider | Mistral |
| Model ID | mistral-small-3-1 |
| Input Price | $0.2 / 1M tokens |
| Output Price | $0.6 / 1M tokens |
| Context Window | 128K tokens |
| Max Output | 4K tokens |
| Capabilities | textfunction_calling |
| Release Date | 2025-03 |
Monthly Cost Estimates
Estimated monthly costs based on different daily usage levels (assuming 50% input / 50% output split).
| Daily Tokens | Monthly Cost | Annual Cost |
|---|---|---|
| 10K | $0.12 | $1.44 |
| 50K | $0.60 | $7.20 |
| 100K | $1.20 | $14.40 |
| 500K | $6.00 | $72.00 |
| 1.0M | $12.00 | $144.00 |
About Mistral Small 3.1
Mistral Small 3.1 is a large language model by Mistral. It features a 128K token context window with up to 4K tokens of output per request. The model supports 2 capabilities: text, function_calling.
At $0.2 per million input tokens and $0.6 per million output tokens, Mistral Small 3.1 is positioned as a cost-effective option in the Mistral lineup. Use our Token Counter to estimate how many tokens your prompts use, and our Pricing Calculator to compare costs across all models.
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FAQ
How much does Mistral Small 3.1 cost?
Mistral Small 3.1 costs $0.2 per million input tokens and $0.6 per million output tokens. For a typical workload of 100K tokens/day, expect approximately $1.50/month.
What is Mistral Small 3.1's context window?
Mistral Small 3.1 supports a context window of 128K tokens. This means your combined input prompt and output response can be up to 128K tokens. The maximum output per response is 4K tokens.
Is Mistral Small 3.1 good for my use case?
Mistral Small 3.1 supports text, function_calling. As a budget-friendly model, it works well for high-volume tasks like classification, summarization, and simple generation. Use our Pricing Calculator to compare with alternatives.