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Mistral: Mistral Large 3 2512 (batch)
mistralai/mistral-large-2512:batchTry Mistral: Mistral Large 3 2512 (batch) now
Runs on your balance at the prices above. New accounts start with free usage.
One API. Every model.
Session cost $0.00
Settings
Advanced parameters
Mistral: Mistral Large 3 2512 (batch) at a glance
- Input price is 44% lower than the median of 434 Text models.
- Context window of 262,144 tokens, enough for long documents and multi-turn conversations.
- Supports tool (function) calling for agents and integrations.
- Supports structured JSON output with a schema.
- Accepts images as input (vision).
- A typical request (1,000 input / 500 output tokens) costs about $0.00219.
About Mistral: Mistral Large 3 2512 (batch)
Mistral: Mistral Large 3 2512 (batch) is a text generation model from Mistral. According to Mistral, it is the company's most capable model to date, built on a sparse mixture-of-experts architecture with 41B active parameters out of 675B total, and released under the Apache 2.0 license. The provider release date is 2025-12-01. The ":batch" suffix in the model id indicates this is the batch variant of the model on api14.
The model accepts text, images and files as input, and produces text as output. Its context window is 262,144 tokens, and the maximum output is 209,715 tokens. That combination of a large context and a large output ceiling means you can feed in long documents, codebases, transcripts or image sets and still leave substantial room for the model's response. Supported request parameters include frequency_penalty, max_tokens, presence_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools and top_p.
Those capabilities point to a fairly wide set of practical uses. The long context suits summarisation and question answering over lengthy documents, contract or report analysis, and multi-file code review. Image input makes it usable for tasks that mix screenshots, diagrams or scanned pages with text instructions. Tool calling and structured outputs fit agent-style workflows and pipelines that need machine-readable responses, such as extracting fields into JSON or routing requests between services. The seed and temperature controls help when you want reproducible or tightly constrained generations.
You call the model through api14's OpenAI-compatible API using the model id "mistralai/mistral-large-2512:batch". Because the interface follows the OpenAI chat completions shape, you send your messages in the usual way and set the model field to that id. You can pass any of the supported parameters listed above in the request body: frequency_penalty, max_tokens, presence_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools and top_p. The batch variant is the one to select when you want this model served in batch mode rather than interactively.
One thing to keep in mind is the output ceiling: maxOutput is 209,715 tokens, so very large single responses are possible but still bounded. If your workload is purely text and does not need image or file input, a smaller text-only model may be a better fit. If you need modalities beyond text output, this model does not provide them, since text is its only output modality.
How to call the Mistral: Mistral Large 3 2512 (batch) API
- Create an API key in your dashboard.
- Install the official openai SDK for your language.
- Set baseURL to https://api14.com/api/v1 and model to "mistralai/mistral-large-2512:batch".
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const result = await client.chat.completions.create({
"model": "mistralai/mistral-large-2512:batch",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
Supported parameters
frequency_penaltymax_tokenspresence_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_pSpecifications
- Context length
- 262,144
- Max output
- 209,715
- Input
- text, image, file
- Output
- text
Requests on api14 · last 7 days
Mistral: Mistral Large 3 2512 (batch): frequently asked questions
- How much does the Mistral: Mistral Large 3 2512 (batch) API cost?
- Mistral: Mistral Large 3 2512 (batch) costs Input $0.88 / 1M tokens. It is charged from your USD balance only for successful requests; failed requests are free.
- What is the context window of Mistral: Mistral Large 3 2512 (batch)?
- Mistral: Mistral Large 3 2512 (batch) reads up to 262,144 tokens per request: prompt, history and documents together. It writes up to 209,715 output tokens per response.
- What can Mistral: Mistral Large 3 2512 (batch) do?
- Mistral: Mistral Large 3 2512 (batch) accepts text, image, file and returns text. It supports tool calling, structured JSON output.
- How do I call Mistral: Mistral Large 3 2512 (batch) from my code?
- Point any OpenAI SDK at https://api14.com/api/v1 and set the model to "mistralai/mistral-large-2512:batch". No other code changes. Copy a ready example from the code panel on this page.
- What are alternatives to Mistral: Mistral Large 3 2512 (batch)?
- Comparable Text models at a similar price: Inception: Mercury 2, Qwen: Qwen3 VL 8B Instruct, OpenAI: GPT-4.1 Mini (batch). Each runs through the same API key, so switching is one string.
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