Mistral: Ministral 8BWork with me

Mistral: Ministral 8B

byMistral

Ministral 8B is a language model from Mistral released on Oct 1, 2024. It reads text and writes text, with a 262K token context window and up to 33K tokens per reply.

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It costs $0.15 per million input tokens and $0.15 per million output tokens. Cached input bills at $0.075, 50% less than fresh input.

It supports tool calling, structured JSON output and prompt caching, and its weights are open, so you can host it yourself.

9 providers serve it, including Vercel AI Gateway, DevPass (LLM Gateway) and Eden AI. The lowest input price is $0.10 per million tokens at Mistral.

On the Artificial Analysis Intelligence Index it scores 5.5, which places it at number 42 among the 43 models I track with independent scores.

Modalities
In / out price
$0.15 / $0.15 per 1M
Context
262K
Max output
33K
Released
Oct 1, 2024
Knowledge cutoff
n/a
  • Tool calling
  • Structured output
  • Reasoning
  • Prompt caching
  • Open weights
  • Free to use

Ministral 8B pricing

USD, as listed on Oct 15, 2026. Most bills are input heavy, so the cached input rate matters as much as the headline price.

Input$0.15 / 1M tokens
Output$0.15 / 1M tokens
Cached input (read)$0.075 / 1M tokens

Ministral 8B providers

9 providers serve it, including Vercel AI Gateway, DevPass (LLM Gateway) and Eden AI. The lowest input price is $0.10 per million tokens at Mistral. Each host sets its own price and limits, so the cheapest one is not always the one with the longest context.

ProviderInput /MOutput /MCache read /MContextMax output
Mistral First party$0.10$0.10–262K128K
Vercel AI Gateway$0.10$0.10–262K128K
DevPass (LLM Gateway)$0.15$0.15–262K8K
Eden AI$0.15$0.15$0.015262K210K
Kilo Gateway$0.15$0.15$0.015262K210K
LLM Gateway$0.15$0.15–262K262K
NanoGPT$0.15$0.15$0.075262K33K
Cortecs$0.179$0.179$0.017256K256K
AI/ML API$0.4126$0.4126$0.0206262K210K

What Ministral 8B costs per month

Pick a workload close to yours or type your own volumes.

Ministral 8B per month
$9.45
Without caching
$12.82
Per request
$0.0003

Independent benchmarks

Measured by third parties, not reported by Mistral. Each links to its source and shows the date I checked it.

Supported request parameters

What you can set when you call Ministral 8B through an OpenAI compatible API.

  • Toolstools
  • Structured outputsstructured_outputs
  • Temperaturetemperature

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All Mistral models

Ministral 8B questions

How much does the Ministral 8B API cost?

$0.15 per million input tokens and $0.15 per million output tokens, with cached input at $0.075. The estimator on this page turns that into a monthly bill for your own workload.

What is the context window of Ministral 8B?

262,144 tokens of input, and it can write up to 32,768 tokens in one reply. As a rough guide, a million tokens is around 750,000 English words.

Which providers serve Ministral 8B?

9 providers serve it, including Vercel AI Gateway, DevPass (LLM Gateway) and Eden AI. The lowest input price is $0.10 per million tokens at Mistral. Prices differ by host, so the Providers table on this page lists each one with its input and output price.

Does Ministral 8B support tool calling?

Yes. It accepts tool definitions and can return JSON that matches a schema, which is what an agent needs to call your APIs.

Is Ministral 8B open source?

Its weights are published, so you can run it on your own hardware or a cloud of your choice. Read the license before commercial use.

When was Ministral 8B released?

Oct 1, 2024.

How good is Ministral 8B compared with other models?

It scores 5.5 on the Artificial Analysis Intelligence Index. Benchmarks are a shortlist, not a verdict: test the top two or three candidates on your own tasks before you commit.

Catalog data from models.dev (MIT licensed), refreshed daily, last on Oct 15, 2026. Independent scores from my hand checked rankings, sources linked above. The summary is written from these facts.

Building on Ministral 8B?

I test your real tasks on it and the two closest alternatives, then ship the agent on whichever wins on cost and accuracy.

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