Fast ve very cheap
$0.03 per 1M input tokens, for steps that run millions of times. hakkında için 360 tokens a second in our tests,
The Ministral 3 3B API: Mistral AI's smallest open-weight model, with vision, for fast, high-volume work, 70% below Mistral's liste fiyatı
ministral-3-3bfrom 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="")Temel URL https://api.zurelay.com/v1. Tüm OpenAI SDK'ları ile uyumludur. Sohbet API dokümanları
Fiyatlandırma
Abonelik olmadan, ön ödemeli bakiyenizden kullandıkça ödeyin. $10'dan başlayan tutarlarla bakiye yükleyin. Başarısız istekler asla ücretlendirilmez.
| Birim fiyat | Zurelay | Mistral AI liste fiyatı | Tasarrufunuz |
|---|---|---|---|
Girdi 1M tokens başına | $0.03 | 70%indirim | |
Çıktı 1M tokens başına | $0.03 | 70%indirim |
Her istem uzunluğunda tek fiyat, up to the full 128K context window. Akış, araç çağrıları ve yapılandırılmış çıktılar için ek ücret alınmaz.
Kaydırıcıları aylık kullanımınıza göre ayarlayın.
Yılda $50.40
Genel bakış
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 ve images, made for fast, low-cost work such as classification, extraction, translation ve 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 ve 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 için 1M çıktı token'ının maliyeti $0.03 per 1M input tokens and $0.03.
Mistral built Ministral 3 for edge ve local use, ve 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 ve ahead of Gemma 3 4B (49.1), ve 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 ve while streaming, ve 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.
Güçlü yönler
$0.03 per 1M input tokens, for steps that run millions of times. hakkında için 360 tokens a second in our tests,
A 0.4B-parameter vision encoder reads photos, screenshots ve scans next to your text, for captions ve quick visual checks.
Fonksiyon çağırma ve JSON output that Mistral describes as native, for routing, extraction ve small agent steps.
Zurelay carries over to a local copy later. sorudan Apache 2.0 weights on Hugging Face, small enough for 8GB üzerinde GPU memory, so what you build
Kullanım alanları
Sort tickets, tag content ve pick the next step in a pipeline, with JSON schema output for the code that follows.
a very low price per call. için Pull fields from text, forms ve screenshots into JSON
Quick translation between the languages Mistral lists, including English, French, Spanish, German, Chinese, Japanese ve Arabic.
Short descriptions ve alt text for photos ve screenshots at volume.
Başlayın
Bekleme listesi ve yeni SDK yok. Kodunuz OpenAI ile çalışıyorsa Zurelay ile de çalışır.
Sign up, add credit ve create an API key. Set a monthly budget or a rate limit per key if you like.
Change the base URL. Everything else in your code stays the same.
https://api.zurelay.com/v1Send chat completions as usual. Streaming, tool calls ve usage reporting work as you expect.
ministral-3-3bZaten kullandığınız araçlarla çalışır
Karşılaştırın
1M token başına $0.06 / $0.06
twice the price per token. için 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 API1M token başına $0.07 / $0.22
Pick Qwen 3.8 Flash for a 1M-token context, video input ve a thinking mode when a task needs more than a small model.
Qwen 3.8 Flash API1M token başına $0.03 / $0.12
Pick DeepSeek V4.1 Flash for a 1M-token context ve thinking on harder text and image tasks.
DeepSeek V4.1 Flash APISSS
Başka sorunuz var mı? Ekibimize sorun, e-postayla yanıtlayalım.
On Zurelay, ministral-3-3b costs $0.03 per 1M input tokens ve $0.03 per 1M output tokens. Mistral's list price is $0.10 input ve $0.10 output per 1M, so you save 70%. One rate applies at every prompt length, and failed requests are never billed.
Install the official openai package, set base_url to https://api.zurelay.com/v1 ve 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 ve ministral-3b. Mistral recommends a temperature of 0.1 or lower for production work.
On Zurelay a request holds up to 131,072 tokens. Mistral lists a 256K window on its own API. The model reads text ve images ve writes text.
It reads görsels: send them in image_url parts, as https links or base64 data URLs, ve 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.
No. Zurelay serves the instruct model, which answers directly, so reasoning_effort has no effect ve there are no reasoning tokens ile 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. arası
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, ve tool_choice "none" works. Tool call ids must be at least 9 characters long, as the model's own ve OpenAI's are. For JSON, send response_format with json_object or json_schema and the answer comes back as JSON.
Both read text ve images, hold 131,072 tokens on Zurelay ve 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.
Its weights are open under the Apache 2.0 license, which allows commercial use ve changes. Mistral publishes base, instruct ve 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.
Yes. Requests for ministral-3-3b run on Mistral AI's Ministral 3 3B Instruct, ve 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, ve 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.
Saniyeler içinde bir anahtar oluşturun, kullandığınız SDK'yı Zurelay'e yönlendirin ve ilk tokendan itibaren her istekte %90'a varan tasarruf sağlayın.