Mistral Small 4 API cost
At list prices from Mistral AI, Mistral Small 4 costs $0.15 per million input tokens and $0.60 per million output tokens. Across the standard workloads below it would cost from $30.80 a month (long-form writing) to $401.50 a month (bulk tagging).
It is the 3rd cheapest of 13 models at every one of them. Output tokens are 89% of the bill for long-form writing but 6.2% for long-document questions. No batch figure can be shown for any of these workloads: there is no verified batch input and batch output prices for this model yet. Cached-prompt assistant is not priced: no verified cached input price for this model yet.
Prices on this page last verified on Sources
Published prices
Mistral AI list prices per million tokens. In our efficient tier.
| Prompt length | Input | Cached input | Output | Batch input | Batch cached input | Batch output |
|---|---|---|---|---|---|---|
| All prompt lengths | $0.15 | n/a | $0.60 | n/a | n/a | n/a |
Cost at five standard workloads
The same traffic on every model, so the rank shows where Mistral Small 4 sits. “vs cheapest” compares it with the cheapest model for that workload.
| Workload | Requests a day | Tokens in / out | Per 1,000 requests | Per month | Via batch API | Rank, all models | Rank, efficient tier | vs cheapest |
|---|---|---|---|---|---|---|---|---|
| Short chat | 10,000 | 1,000 / 300 | $0.33 | $100.38 | No verified batch input, batch output price for this model yet. | 3rd of 13 | 3rd of 5 | 1.3× (Claude Haiku 5.5) |
| Long-document questions | 1,000 | 30,100 / 500 | $4.81 | $146.46 | No verified batch input, batch output price for this model yet. | 3rd of 13 | 3rd of 5 | 1.5× (Claude Haiku 5.5) |
| Bulk tagging | 200,000 | 400 / 10 | $0.066 | $401.50 | No verified batch input, batch output price for this model yet. | 3rd of 13 | 3rd of 5 | 1.5× (Claude Haiku 5.5) |
| Long-form writing | 500 | 1,500 / 3,000 | $2.03 | $30.80 | No verified batch input, batch output price for this model yet. | 3rd of 13 | 3rd of 5 | 1.2× (Claude Haiku 5.5) |
| Cached-prompt assistant | 20,000 | 8,000 / 400 | No verified cached input price for this model yet. |
Equal costs share a rank. “Via batch API” prices the same traffic with every request sent through the provider’s batch API, using its published batch prices.
Workload assumptions
Short chat
Short questions and answers at moderate volume.
| Part of the prompt | Tokens | Cached | Why |
|---|---|---|---|
| Instructions | 300 | No | Short instructions, treated as uncached. |
| Message and recent turns | 700 | No | Changes with every request. |
| Total | 1,000 | None cached |
- Requests a day: 10,000
- A popular in-app assistant.
- Output tokens per request: 300
- A reply of about 220 words.
- Batch API: not used
- Real-time replies.
These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.
Long-document questions
Long input with a short answer: most of the cost is input tokens.
| Part of the prompt | Tokens | Cached | Why |
|---|---|---|---|
| Document | 30,000 | No | About 22,000 words, different every time. |
| Question | 100 | No | One or two sentences. |
| Total | 30,100 | None cached |
- Requests a day: 1,000
- A research or legal team asking questions of whole documents.
- Output tokens per request: 500
- An answer of about 370 words.
- Batch API: not used
- Real-time answers.
These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.
Bulk tagging
Very high volume with a tiny output: a label per item.
| Part of the prompt | Tokens | Cached | Why |
|---|---|---|---|
| Instructions and labels | 300 | No | Short instructions, treated as uncached. |
| Item | 100 | No | A short text. |
| Total | 400 | None cached |
- Requests a day: 200,000
- Items such as tickets, reviews or records tagged as they arrive.
- Output tokens per request: 10
- One label.
- Batch API: not used
- Tagged as items arrive.
These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.
Long-form writing
A short brief and a long answer: most of the cost is output tokens.
| Part of the prompt | Tokens | Cached | Why |
|---|---|---|---|
| Brief and style notes | 1,500 | No | Different for each piece. |
| Total | 1,500 | None cached |
- Requests a day: 500
- Articles, reports or long emails drafted a day.
- Output tokens per request: 3,000
- About 2,200 words.
- Batch API: not used
- Drafts are wanted straight away.
These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.
Cached-prompt assistant
A large fixed prompt read from the prompt cache on every request.
| Part of the prompt | Tokens | Cached | Why |
|---|---|---|---|
| Instructions and tool definitions | 6,000 | Yes | The same on every request, so read from the prompt cache. |
| Conversation and request | 2,000 | No | Changes with every request. |
| Total | 8,000 | 75% cached |
- Requests a day: 20,000
- A busy assistant with long instructions and tool definitions.
- Output tokens per request: 400
- A reply of about 300 words.
- Batch API: not used
- Real-time replies.
These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.
Your traffic looks different? Enter your own figures in the calculator.
Related pages
Other models in the same tier
Sources
Sources: docs.mistral.ai (checked )
- Tier: Provider text: "Hybrid model unifying instruct, reasoning, and coding in a single efficient model." Described as efficient: efficient. docs.mistral.ai (checked )
Prices are list prices as each provider publishes them, used unchanged. How the figures are calculated: methodology.