Strong for its size
0.551 on Arena Hard e 68.5 on WildBench in Mistral's tests, ahead of Qwen3 14B e Gemma 3 12B, and comparable to Mistral Small 3.2 24B by Mistral's account.
Preço de tabela de The Ministral 3 14B API: the largest Ministral 3 model, with vision e tool calling, 70% below Mistral's
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="")URL base https://api.zurelay.com/v1. Funciona com qualquer SDK da OpenAI. Documentação da API Chat
Preços
Pague apenas o que utilizar com saldo pré-pago, sem subscrição. Carregue a partir de $10. Os pedidos que falham nunca são cobrados.
| Preço | Zurelay | Preço de tabela de Mistral AI | Poupa |
|---|---|---|---|
Entrada por 1M tokens | $0.06 | 70%de desconto | |
Saída por 1M tokens | $0.06 | 70%de desconto |
A mesma tarifa para qualquer comprimento de prompt, up to the full 128K context window. O streaming, as chamadas de ferramentas e as saídas estruturadas não têm custos adicionais.
Ajuste os controlos deslizantes ao seu consumo mensal.
$100.80 por ano
Visão geral
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 e 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, em 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 e 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 custa $0.06 per 1M input tokens and $0.06 por 1M tokens de saída.
Mistral built Ministral 3 for edge e local use, e 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 e 0.904 on MATH, ahead of Qwen3 14B without thinking (0.427, 65.1 e 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 e while streaming, e 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.
Pontos fortes
0.551 on Arena Hard e 68.5 on WildBench in Mistral's tests, ahead of Qwen3 14B e Gemma 3 12B, and comparable to Mistral Small 3.2 24B by Mistral's account.
8.49 em MM MTBench in Mistral's tests. Send screenshots, charts e photos next to your text.
Calls several tools at once, also while streaming, e follows a JSON schema, for agent steps e extraction.
Apache 2.0 weights on Hugging Face that fit in 24GB de GPU memory em FP8, so what you build on Zurelay carries over to a self-hosted copy later.
Casos de uso
Customer-facing chat e internal assistants that need good everyday answers em a very low price per token.
Tool-calling steps such as looking things up, filling forms e choosing the next action, with JSON for the code that follows.
Pull fields from emails, documents e screenshots into a JSON schema.
Translate, summarize e answer in the languages Mistral lists, from French e German to Chinese, Japanese and Arabic.
Começar
Sem lista de espera nem um novo SDK. Se o seu código já comunica com a OpenAI, também comunica com a Zurelay.
Sign up, add credit e 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 e usage reporting work as you expect.
ministral-3-14bFunciona com as ferramentas que já usa
Comparar
$0.03 / $0.03 por 1M tokens
Pick Ministral 3 3B for the simplest, highest-volume steps em half the price per token, about twice as fast in our tests.
API de Ministral 3 3B$0.07 / $0.22 por 1M tokens
Pick Qwen 3.8 Flash for a 1M-token context, video input e a thinking mode when a task needs more than a small model.
API de Qwen 3.8 Flash$0.10 / $0.59 por 1M tokens
Pick Gemini 3.1 Flash-Lite for Google's low-cost model with a 1M-token context e audio, video and PDF input.
API de Gemini 3.1 Flash-LitePerguntas frequentes
Mais alguma dúvida? Fale com a nossa equipa e responderemos por email.
On Zurelay, ministral-3-14b costs $0.06 per 1M input tokens e $0.06 per 1M output tokens. Mistral's list price is $0.20 input e $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 e 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 e 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 e images e writes text.
It reads imagems: send them in image_url parts, as https links or base64 data URLs, e 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 e there are no reasoning tokens a 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.
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, e tool_choice "none" works. Tool call ids must be at least 9 characters long, as the model's own e OpenAI's are. For JSON, send response_format with json_object or json_schema and the answer comes back as JSON.
Both read text e images, hold 131,072 tokens on Zurelay e 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 e changes. Mistral publishes base, instruct e 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, e 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, e 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.
Crie uma chave em segundos, configure o SDK que já usa para aceder à Zurelay e cada pedido custa até 90% menos desde o primeiro token.