Mistral Small 4 API Pricing
Mistral Small 4 is the cheap multimodal Mistral tier, and it just got less cheap: $0.15/M input and $0.60/M output, against $0.10 / $0.30 before. Input is up 1.5x and output has doubled, with no announcement on the vendor's page - the card simply shows different numbers. It remains an Apache 2.0 open-weight model, described by Mistral as a hybrid unifying instruct, reasoning and coding.
Mistral Small 4 API cost calculator.
Calculator pre-loaded with current Mistral Small 4 rates from Mistral's pricing page. Tweak spend or output mix to compare this model with nearby alternatives.
Mistral Small 4 cost on real workloads.
Repo-wide bug fix
Reading 100-page contracts
Support agent ticket triage
Research planning turn
Counts use a chars-per-token calibration measured on the vendor's own published tokenizer (mistralai/Mistral-Nemo-Instruct-2407, 2026-06-10). English prose is typically within a few percent; code and non-Latin scripts tokenize heavier. For billing-exact counts use the vendor's count-tokens API.
| Model | Input /M | Output /M | Effective blended | Context | Best for |
|---|---|---|---|---|---|
| Mistral Small 4 Current | $0.15 cache $0.015 | $0.60 | $0.0842 agentic 92/8 | 256K | Low-cost Mistral workloads |
| Mistral Large 3 | $0.50 cache $0.05 | $1.50 | $0.241 +2.9× | documented elsewhere — not on pricing page | Open-weight multimodal work |
| Mistral Medium 3.5 | $1.50 cache $0.15 | $7.50 | $0.962 +11× | documented elsewhere — not on pricing page | Agentic and coding workloads |
| GPT-6.1 Terra | $1.00 cache $0.05 | $5.00 | $0.645 +7.7× | 1.05M | OpenAI's fast, efficient GPT-6 tier |
| Claude Sonnet 5.5 | $2.00 cache $0.10 | $10.00 | $1.29 +15× | 1M | Anthropic's current Sonnet |
By comparison
Mistral Small 4 API pricing FAQ.
Short answers for teams checking Mistral Small 4 pricing, status, and migration choices.
Q · 01 Is Mistral Small 4 still available? +
mistral-small-latest.Q · 02 How much does Mistral Small 4 cost? +
Q · 03 Is cached-input pricing included? +
$0.015/M, 10% of the input rate. The calculator defaults to an 82% cache-hit rate, the assumption used across AI//COST; set it to 0% for workloads with no repeated prompt prefix.Q · 04 What should teams compare it against? +
current same-provider models.