Mistral AI · LLM API pricing
Ministral 3B API pricing: cheapest provider
2 providers sell Ministral 3B. Microsoft Azure AI Foundry is cheapest; the most expensive charges 2.5× as much for the same model.
- Cheapest$0.04per 1M · Microsoft Azure AI Foundry
- Input · output$0.04 / $0.04per 1M tokens
- Price gap2.5×across 2 providers
- Context131Kmax tokens
Standard list prices in USD from each provider's pricing page · last price change Sep 28, 2026 · How we collect and rank prices
Ranked for your volume
Ministral 3B monthly cost by provider
Change the monthly tokens and the ranking updates instantly, using each provider's standard list price.
More requirements: caching, context, features, provider
| Provider | Estimated / month | Input / 1M | Output / 1M | Cached input / 1M | Context |
|---|---|---|---|---|---|
1 Microsoft Azure AI FoundryCloud platform - lowest for your volumePricing page | $0.48 | $0.04 | $0.04 | Not listed | 128,000 |
2 Mistral AIModel developerPricing page | $1.20 | $0.10 | $0.10 | $0.01 | 131,072 |
Order depends on listed price for your volume only. No provider pays for its position.
Input volume includes the cached share, not an additional token volume. This is a list-price estimate, not a quote: cache-write charges, cache eligibility/TTL, batch discounts, long-context surcharges, regional pricing and taxes are excluded. Check the provider's terms for your workload before switching.
Price history
The cheapest price has not changed since tracking started on Sep 28, 2026: $0.04 per 1M tokens at Microsoft Azure AI Foundry. All price changes
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Before you pick a provider
Microsoft Azure AI Foundry lists Ministral 3B 60% below the developer's own API (Mistral AI) on a blended basis. Check rate limits, data retention and model quantization before switching.
Context windows differ by provider, from 128K to 131K tokens. A cheaper host may not accept your longest prompts.
1 of 2 providers list a cached-input price. Repeated system prompts or documents can cost much less there than the standard input rate shown above.
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