Mistral: Ministral 14B
Ministral 14B is a language model from Mistral released on Dec 2, 2025. 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 $0.20 per million input tokens and $0.20 per million output tokens. Cached input bills at $0.10, 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.
10 providers serve it, including Vercel AI Gateway, DevPass (LLM Gateway) and Eden AI.
On the Artificial Analysis Intelligence Index it scores 6, which places it at number 41 among the 43 models I track with independent scores.
- Modalities
- In / out price
- $0.20 / $0.20 per 1M
- Context
- 262K
- Max output
- 33K
- Released
- Dec 2, 2025
- Knowledge cutoff
- n/a
- Tool calling
- Structured output
- Reasoning
- Prompt caching
- Open weights
- Free to use
Ministral 14B 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 | $0.20 / 1M tokens | |
|---|---|---|
| Output | $0.20 / 1M tokens | |
| Cached input (read) | $0.10 / 1M tokens | 50% off input |
Ministral 14B providers
10 providers serve it, including Vercel AI Gateway, DevPass (LLM Gateway) and Eden AI. Each host sets its own price and limits, so the cheapest one is not always the one with the longest context.
| Provider | Input /M | Output /M | Cache read /M | Context | Max output |
|---|---|---|---|---|---|
| Vercel AI Gateway | $0.20 | $0.20 | $0.02 | 262K | 256K |
| DevPass (LLM Gateway) | $0.20 | $0.20 | – | 262K | 8K |
| Eden AI | $0.20 | $0.20 | $0.02 | 262K | 210K |
| Kilo Gateway | $0.20 | $0.20 | $0.02 | 262K | 210K |
| LLM Gateway | $0.20 | $0.20 | – | 262K | 262K |
| NanoGPT | $0.20 | $0.20 | $0.10 | 262K | 33K |
| Pioneer | $0.20 | $0.20 | $0.20 | 256K | 131K |
| Cortecs | $0.24 | $0.24 | $0.022 | 256K | 256K |
| 302.AI | $0.33 | $0.33 | – | 128K | 128K |
| AI/ML API | $0.4814 | $0.4814 | $0.0275 | 262K | 210K |
What Ministral 14B costs per month
Pick a workload close to yours or type your own volumes.
Independent benchmarks
Measured by third parties, not reported by Mistral. Each links to its source and shows the date I checked it.
A composite of 10 independent evaluations (agents 30%, coding 20%, scientific reasoning 20%, general 30%), run by Artificial Analysis on each model, version 4.3.2.
Artificial Analysis, checked Oct 10, 2026
Median output tokens per second measured by Artificial Analysis on the provider API, for the same model setting as its index score.
Artificial Analysis, checked Oct 10, 2026
Benchmarks Mistral reports (1)
Labs pick their own settings and harnesses, so compare these only within one lab.
Supported request parameters
What you can set when you call Ministral 14B through an OpenAI compatible API.
- Tools
tools - Structured outputs
structured_outputs - Temperature
temperature
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Ministral 14B questions
How much does the Ministral 14B API cost?
$0.20 per million input tokens and $0.20 per million output tokens, with cached input at $0.10. The estimator on this page turns that into a monthly bill for your own workload.
What is the context window of Ministral 14B?
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 14B?
10 providers serve it, including Vercel AI Gateway, DevPass (LLM Gateway) and Eden AI. Prices differ by host, so the Providers table on this page lists each one with its input and output price.
Does Ministral 14B 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 14B 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 14B released?
Dec 2, 2025.
How good is Ministral 14B compared with other models?
It scores 6 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 14B?
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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