Fast 和 very cheap
$0.03 per 1M input tokens, for steps that run millions of times.：关于 360 tokens a second in our tests,
Mistral AI
运行正常· 每隔几分钟检查一次Ministral 3 3B API
The Ministral 3 3B API: Mistral AI's smallest open-weight model, with vision, for fast, high-volume work, 70% below Mistral's 原价
每 1M token 价格70%优惠
- 输入
- $0.03
$0.10 - 输出
- $0.03
$0.10
模型 ID
ministral-3-3bchat.py
from openai import OpenAIclient = OpenAI( base_url="https://api.zurelay.com/v1", api_key="YOUR_ZURELAY_KEY",)stream = client.chat.completions.create( model="ministral-3-3b", messages=[{"role": "user", "content": "Explain quicksort in two sentences."}], stream=True,)for chunk in stream: if chunk.choices: print(chunk.choices[0].delta.content or "", end="")Base URL https://api.zurelay.com/v1. 支持任意 OpenAI SDK。 Chat API 文档
- 上下文窗口
- 128K tokens
- 推理
- 无
- 输入
- Text, Image
- 发布日期
- 2025年12月2日
- 状态
- 运行正常
价格
Ministral 3 3B API 价格。 仅需官方定价的一小部分。
从预付余额中按量扣费，无需订阅。$10 起充。请求失败不收费。
| 单价 | Zurelay | Mistral AI 原价 | 节省金额 |
|---|---|---|---|
输入 每 1M tokens | $0.03 | 70%优惠 | |
输出 每 1M tokens | $0.03 | 70%优惠 |
所有提示词长度均采用同一费率, up to the full 128K context window。流式输出、工具调用和结构化输出不额外收费。
省钱计算器
拖动滑块设置每月用量。
每月输入 token 数50M
每月输出 token 数10M
Zurelay
$1.80
Mistral AI 原价
$6.00
每月节省$4.20
每年 $50.40
概览
Ministral 3 3B 是什么?
Ministral 3 3B is the smallest model in Mistral AI's Ministral 3 family, released on December 2, 2025: an open-weight model that reads text 和 images, made for fast, low-cost work such as classification, extraction, translation 和 image captions. The Zurelay Ministral 3 3B API serves its instruct version through one OpenAI-compatible endpoint with a 131,072-token context window, at 70% below Mistral's list price.
Mistral AI released the Ministral 3 family on December 2, 2025, alongside Mistral Large 3, in three sizes: 3B, 8B 和 14B. Each size comes as a base, an instruct and a reasoning model, all with image understanding and all under the Apache 2.0 license, with the weights on Hugging Face. Ministral 3 3B pairs a 3.4B-parameter language model with a 0.4B-parameter vision encoder, and Mistral says it fits in 8GB of GPU memory at FP8. On Zurelay the model ID is ministral-3-3b, and it 每 1M 输出 token 的费用为 $0.03 per 1M input tokens and $0.03。
Mistral built Ministral 3 for edge 和 local use, 和 points the 3B model at lightweight, real-time work: image captions, text classification, translation, data extraction and short content. It handles dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean and Arabic. Mistral says its Ministral instruct models often write an order of magnitude fewer tokens than comparable models.
On Mistral's model card the instruct model scores 56.8 on WildBench, level with Qwen3-VL-4B-Instruct 和 ahead of Gemma 3 4B (49.1), 和 0.830 on MATH, ahead of Gemma 3 4B (0.759) and behind Qwen3-VL-4B-Instruct (0.900). Qwen3-VL-4B-Instruct also leads it on Arena Hard, 0.438 against 0.305. These are Mistral's numbers, not independent ones.
The instruct model answers directly without reasoning first, so reasoning_effort has no effect. It calls tools, several at once 和 while streaming, 和 returns JSON for json_object or json_schema in response_format. Mistral lists a 256K context window on its own API; on Zurelay a request holds up to 131,072 tokens. In our tests it wrote about 360 tokens a second and knew little about events after 2024, as small models tend to, so put the facts it needs in the prompt. You pay $0.03 per 1M input tokens and $0.03 per 1M output tokens against Mistral's list price of $0.10 and $0.10.
优势
Ministral 3 3B 的出色之处。 以及团队用它构建的应用。
图像理解
A 0.4B-parameter vision encoder reads photos, screenshots 和 scans next to your text, for captions 和 quick visual checks.
工具 和 JSON
函数调用 和 JSON output that Mistral describes as native, for routing, extraction 和 small agent steps.
开放权重
Hugging Face, small enough for 8GB / GPU memory, so what you build on Zurelay carries over to a local copy later. 上的 Apache 2.0 weights
使用场景
分类与路由
Sort tickets, tag content 和 pick the next step in a pipeline, with JSON schema output for the code that follows.
信息提取
a very low price per call.：Pull fields from text, forms 和 screenshots into JSON
Translation
Quick translation between the languages Mistral lists, including English, French, Spanish, German, Chinese, Japanese 和 Arabic.
Image captions
Short descriptions 和 alt text for photos 和 screenshots at volume.
开始使用
三步调用 Ministral 3 3B。
无需排队，也无需换用新的 SDK。只要你的代码能调用 OpenAI, 就能调用 Zurelay。
- 1
创建密钥
Sign up, add credit 和 create an API key. Set a monthly budget or a rate limit per key if you like.
- 2
Zurelay：Point your SDK
Change the base URL. Everything else in your code stays the same.
https://api.zurelay.com/v1 - 3
Use ministral-3-3b
Send chat completions as usual. Streaming, tool calls 和 usage reporting work as you expect.
ministral-3-3b
对比
相似模型。 同一个 key 即可调用。
70%优惠
Ministral 3 14B
每 1M token $0.06 / $0.06
twice the price per token.：Pick Ministral 3 14B, the largest Ministral 3 model, for stronger answers: 0.551 against 0.305 on Arena Hard in Mistral's tests,
Ministral 3 14B API53%优惠
Qwen 3.8 Flash
每 1M token $0.07 / $0.22
Pick Qwen 3.8 Flash for a 1M-token context, video input 和 a thinking mode when a task needs more than a small model.
Qwen 3.8 Flash API90%优惠
DeepSeek V4.1 Flash
每 1M token $0.03 / $0.12
Pick DeepSeek V4.1 Flash for a 1M-token context 和 thinking on harder text and image tasks.
DeepSeek V4.1 Flash APIMinistral 3 3B API 如何收费?
On Zurelay, ministral-3-3b costs $0.03 per 1M input tokens 和 $0.03 per 1M output tokens. Mistral's list price is $0.10 input 和 $0.10 output per 1M, so you save 70%. One rate applies at every prompt length, and failed requests are never billed.
如何通过 OpenAI SDK 调用 the Ministral 3 3B API?
Install the official openai package, set base_url to https://api.zurelay.com/v1 和 use your Zurelay API key. Then send a Chat Completions request with model set to "ministral-3-3b". Zurelay also accepts ministral-3-3b-instruct, mistralai/ministral-3-3b 和 ministral-3b. Mistral recommends a temperature of 0.1 or lower for production work.
Ministral 3 3B context window 是什么?
On Zurelay a request holds up to 131,072 tokens. Mistral lists a 256K window on its own API. The model reads text 和 images 和 writes text.
Can Ministral 3 3B read 张图片s or PDFs?
It reads 张图片s: send them in image_url parts, as https links or base64 data URLs, 和 they count as input tokens. Mistral suggests images close to square, with very wide or thin ones cropped. Zurelay doesn't take PDFs, audio or video for Ministral 3 3B: a request that includes one is turned away with a clear error before anything is billed.
Does Ministral 3 3B reason before it answers?
No. Zurelay serves the instruct model, which answers directly, so reasoning_effort has no effect 和 there are no reasoning tokens 至 pay for. Mistral also publishes a separate Ministral 3 3B Reasoning model, which Zurelay doesn't serve. For answers with thinking, use Qwen 3.8 Flash or DeepSeek V4.1 Flash.
Does Ministral 3 3B support tool calling 和 JSON output?
Yes. Pass tools as you would to any OpenAI model; it can call several at once, also while streaming. A tool forced by name is called, 和 tool_choice "none" works. Tool call ids must be at least 9 characters long, as the model's own 和 OpenAI's are. For JSON, send response_format with json_object or json_schema and the answer comes back as JSON.
Should I use Ministral 3 3B or Ministral 3 14B?
Both read text 和 images, hold 131,072 tokens on Zurelay 和 call tools. 14B pairs a 13.5B-parameter language model with the same 0.4B vision encoder and scores higher in Mistral's tests (0.551 against 0.305 on Arena Hard, 68.5 against 56.8 on WildBench), at twice the price. 3B is faster, about 360 tokens a second against 170 in our tests, and suits simple, high-volume steps.
Is Ministral 3 3B open source?
Its weights are open under the Apache 2.0 license, which allows commercial use 和 changes. Mistral publishes base, instruct 和 reasoning versions on Hugging Face and says the 3B fits in 8GB of GPU memory at FP8. The API is the quick way to use it without running your own hardware.
Is this the real Ministral 3 3B?
Yes. Requests for ministral-3-3b run on Mistral AI's Ministral 3 3B Instruct, 和 Zurelay doesn't swap in a different model. Only smart routing, which you turn on yourself, can answer with a close alternative when the model is down, 和 the x-zurelay-model header names the model that answered. Responses are sampled, so wording varies between runs. Zurelay is independent and is not affiliated with or endorsed by Mistral AI.
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