Strong for its size
0.551 on Arena Hard ve 68.5 on WildBench in Mistral's tests, ahead of Qwen3 14B ve Gemma 3 12B, and comparable to Mistral Small 3.2 24B by Mistral's account.
The Ministral 3 14B API: the largest Ministral 3 model, with vision ve tool calling, 70% below Mistral's liste fiyatı
ministral-3-14bfrom openai import OpenAIclient = OpenAI( base_url="https://api.zurelay.com/v1", api_key="YOUR_ZURELAY_KEY",)stream = client.chat.completions.create( model="ministral-3-14b", 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 | $0.06 | 70%indirim | |
Çıktı 1M tokens başına | $0.06 | 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 $100.80
Genel bakış
70% below Mistral's list price. için Ministral 3 14B is the largest model in Mistral AI's Ministral 3 family, released on December 2, 2025: an open-weight model that reads text ve images and, by Mistral's account, performs comparably to its larger Mistral Small 3.2 24B. The Zurelay Ministral 3 14B API serves its instruct version through one OpenAI-compatible endpoint with a 131,072-token context window,
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 14B pairs a 13.5B-parameter language model with a 0.4B-parameter vision encoder, and Mistral says it fits in 24GB of GPU memory at FP8. On Zurelay the model ID is ministral-3-14b, and it için 1M çıktı token'ının maliyeti $0.06 per 1M input tokens and $0.06.
Mistral built Ministral 3 for edge ve local use, ve points the 14B model at private chat and assistant deployments on limited hardware, local agents and fine-tuning. 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 0.551 on Arena Hard, 68.5 on WildBench ve 0.904 on MATH, ahead of Qwen3 14B without thinking (0.427, 65.1 ve 0.870) and Gemma 3 12B (0.436, 63.2 and 0.854). On MM MTBench, a multimodal chat test, it scores 8.49 against 6.70 for Gemma 3 12B. 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 170 tokens a second and knew little about events after 2024, so put the facts it needs in the prompt. You pay $0.06 per 1M input tokens and $0.06 per 1M output tokens against Mistral's list price of $0.20 and $0.20.
Güçlü yönler
0.551 on Arena Hard ve 68.5 on WildBench in Mistral's tests, ahead of Qwen3 14B ve Gemma 3 12B, and comparable to Mistral Small 3.2 24B by Mistral's account.
MM MTBench in Mistral's tests. Send screenshots, charts ve photos next to your text. üzerinde 8.49
Calls several tools at once, also while streaming, ve follows a JSON schema, for agent steps ve extraction.
GPU memory sorudan FP8, so what you build on Zurelay carries over to a self-hosted copy later. için Apache 2.0 weights on Hugging Face that fit in 24GB
Kullanım alanları
a very low price per token. için Customer-facing chat ve internal assistants that need good everyday answers
Tool-calling steps such as looking things up, filling forms ve choosing the next action, with JSON for the code that follows.
Pull fields from emails, documents ve screenshots into a JSON schema.
Translate, summarize ve answer in the languages Mistral lists, from French ve German to Chinese, Japanese and Arabic.
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-3-14bZaten kullandığınız araçlarla çalışır
Karşılaştırın
1M token başına $0.03 / $0.03
half the price per token, about twice as fast in our tests. için Pick Ministral 3 3B for the simplest, highest-volume steps
Ministral 3 3B 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 $0.10 / $0.59
Pick Gemini 3.1 Flash-Lite for Google's low-cost model with a 1M-token context ve audio, video and PDF input.
Gemini 3.1 Flash-Lite APISSS
Başka sorunuz var mı? Ekibimize sorun, e-postayla yanıtlayalım.
On Zurelay, ministral-3-14b costs $0.06 per 1M input tokens ve $0.06 per 1M output tokens. Mistral's list price is $0.20 input ve $0.20 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-3-14b". Zurelay also accepts ministral-3-14b-instruct, mistralai/ministral-3-14b ve ministral-14b. 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 14B: 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 14B 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 is the stronger model, with a 13.5B-parameter language model against 3.4B, and scores higher in Mistral's tests: 0.551 against 0.305 on Arena Hard and 68.5 against 56.8 on WildBench. 3B costs half as much and was about twice as fast in our tests, so it suits the simplest, highest-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 14B fits in 24GB of GPU memory at FP8. The API is the quick way to use it without running your own hardware.
Yes. Requests for ministral-3-14b run on Mistral AI's Ministral 3 14B 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.