How much does Ministral 3 8B cost?

$0.1500 per million input tokens and $0.1500 per million output tokens. On a typical chat turn of 1,500 input and 300 output tokens that is $0.000270 per request, or $27.00 per month at 100,000 requests. Read from Mistral AI's own documentation on August 5, 2026.

What is the context window of Ministral 3 8B?

256,000 tokens. That budget covers everything in the request — system prompt, conversation history, tool definitions, documents — plus the response itself, not just your input.

Why is output more expensive than input on Ministral 3 8B?

Output costs 1.0 times input here. Input is processed in a single parallel pass, while output is generated one token at a time with a full pass over the model for each. That is why a model that answers concisely can be cheaper in production than one with a lower headline rate.

Mistral AI

Ministral 3 8B pricing

$0.1500 per million input tokens, $0.1500 per million output. 256K token context window. Read from Mistral AI’s own documentation on August 5, 2026.

Input: $0.1500
Cached input: —
Output: $0.1500
Context window: 256K
Token counting: Estimate
Price verified: 2026-08-05

Input and output are priced identically, which is unusual and makes output-heavy work disproportionately cheap here relative to models that charge a premium on output.

Source: Mistral AI pricing documentation. Prices change without notice — verify before committing spend.

What Ministral 3 8B costs on real work

Four workload shapes at 100,000 requests a month. The point of showing four is that the ranking between models changes depending on which one describes you.

Ministral 3 8B cost by workload shape
Workload	In	Out	Per request	Per month
ClassificationShort input, one-word answer. Input-dominated.	500	50	$0.000083	$8.25
Chat turnA system prompt plus a few turns of history.	1,500	300	$0.000270	$27.00
Document summaryA long document in, a paragraph out.	20,000	800	$0.003120	$312.00
Code generationOutput-heavy — where output pricing dominates.	2,000	1,500	$0.000525	$52.50

Put your own numbers in the cost calculator, or measure a real prompt first in the token counter.

Counting tokens for Ministral 3 8B

Mistral AI does not publish a tokenizer that runs in a browser, so any pre-flight count for Ministral 3 8B is an estimate rather than a measurement.

Mistral publishes its Tekken tokenizer only as a Python package, with no browser build. Counted with o200k_base and scaled; Tekken generally produces more tokens than o200k_base on the same English text.

Treat it as accurate to within roughly ten to twenty percent. That is fine for budgeting and wrong for sizing a prompt right at a context window boundary — where precision matters, use Mistral AI’s own token counting endpoint from your backend. The methodology page sets out every scaling factor used here.

Other Mistral AI models

The tier question: is a cheaper model in the same family enough for your task?

Other Mistral AI models compared with Ministral 3 8B
Model	Input	Output	Context	Chat turn
Ministral 3 8B — this page	$0.1500	$0.1500	256K	$0.000270
Mistral Medium 3.5	$1.50	$7.50	256K	$0.004500
Mistral Large 3	$0.5000	$1.50	256K	$0.001200
Mistral Small 4	$0.1500	$0.6000	256K	$0.000405
Magistral Medium	$2.00	$5.00	256K	$0.004500
Devstral 2	$0.4000	$2.00	256K	$0.001200

Alternatives from other providers

Models priced nearest to Ministral 3 8B, not the cheapest on the market — those are the ones actually worth evaluating against it.

Frequently asked questions

How much does Ministral 3 8B cost?: $0.1500 per million input tokens and $0.1500 per million output tokens. On a typical chat turn of 1,500 input and 300 output tokens that is $0.000270 per request, or $27.00 per month at 100,000 requests. Read from Mistral AI's own documentation on August 5, 2026.
Can I count Ministral 3 8B tokens exactly?: No. Mistral AI does not publish a tokenizer that runs in a browser, so any pre-flight count for Ministral 3 8B is an estimate. Mistral publishes its Tekken tokenizer only as a Python package, with no browser build. Counted with o200k_base and scaled; Tekken generally produces more tokens than o200k_base on the same English text. Treat it as accurate to within roughly ten to twenty percent and never as the basis for sizing a prompt right at a context window boundary.
What is the context window of Ministral 3 8B?: 256,000 tokens. That budget covers everything in the request — system prompt, conversation history, tool definitions, documents — plus the response itself, not just your input.
Why is output more expensive than input on Ministral 3 8B?: Output costs 1.0 times input here. Input is processed in a single parallel pass, while output is generated one token at a time with a full pass over the model for each. That is why a model that answers concisely can be cheaper in production than one with a lower headline rate.