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Gemini Embedding 2 vs Mistral Embed 2312: API price, context & features · api14

Google: Gemini Embedding 2 vs Mistral: Mistral Embed 2312

A side-by-side comparison of Google: Gemini Embedding 2 ($0.70 / 1M tokens) and Mistral: Mistral Embed 2312 ($0.35 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Google: Gemini Embedding 2	Mistral: Mistral Embed 2312
Provider	Google	Mistral
Input	$0.70 / 1M tokens	$0.35 / 1M tokens
Audio input	$22.75 / 1M tokens	-
Image	$0.000002 / image	-
Context window	8,192	8,192
Max output	7,372	6,553
Input	text, image, file, audio, video	text
Output	embeddings	embeddings
Tool calling
Structured output
Reasoning control
Added	May 20, 2026	Oct 31, 2025

Key differences

Mistral: Mistral Embed 2312 is 50% cheaper on input tokens.

In depth

Google: Gemini Embedding 2 is an embedding model from Google, and Mistral: Mistral Embed 2312 is an embedding model from Mistral. Both sit in the embeddings category, which means their job is to turn input into vectors you can store, compare and search over rather than to generate chat replies. If you are building retrieval, clustering, deduplication or semantic search, these are the two candidates you are choosing between on api14.

The clearest difference is input modality. Gemini Embedding 2 accepts text, image, file, audio and video, and returns embeddings. Mistral Embed 2312 accepts text only. Both have a context length of 8192 tokens, so the amount of text you can pack into a single request is the same on paper, and neither model exposes supported parameters you can tune. In practice this means the choice is not about how much text fits but about what kind of content you need to embed. If your corpus is plain text, both models can handle it and the context windows line up. If your corpus includes screenshots, scanned pages, audio clips or video frames, only Gemini Embedding 2 covers those inputs directly.

For a developer picking one, start from the data. A text-only pipeline, such as embedding support tickets, documentation pages, product descriptions or chat logs, is a natural fit for Mistral Embed 2312, and it is the cheaper option on input according to the pricing shown on this page. A pipeline that mixes text with images, files, audio or video is a natural fit for Gemini Embedding 2, because Mistral Embed 2312 cannot take those inputs at all. Where both could work, cost is the tiebreaker, and that points to Mistral Embed 2312 on input. Output pricing is not listed as a differentiator, so do not assume one is cheaper on the output side.

Calling either model through api14 works the same way, because the API is OpenAI-compatible. You point your client at the api14 base URL, send your input to the embeddings endpoint, and set the model field. To use Gemini Embedding 2, set the model id to "google/gemini-embedding-2". To use Mistral Embed 2312, set it to "mistralai/mistral-embed-2312". Everything else in the request stays the same, so switching between them is a one-line change and you can benchmark both against your own data before committing.

There is still a case for the other model. If your workload is text only and input cost matters, Mistral Embed 2312 remains the better pick even though Gemini Embedding 2 can also do text. Multimodal capability is only worth paying for if you actually use it.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "google/gemini-embedding-2" to "mistralai/mistral-embed-2312" and prompts, streaming and tools keep working.

Google: Gemini Embedding 2 details & playground →Mistral: Mistral Embed 2312 details & playground →

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api14.com/api/v1",
  apiKey: process.env.API14_API_KEY,
});

const result = await client.embeddings.create({
  "model": "mistralai/mistral-embed-2312",
  "input": [
    "The quick brown fox",
    "Lorem ipsum"
  ]
});
console.log(result.data.map((d) => d.embedding.length));

Google: Gemini Embedding 2 vs Mistral: Mistral Embed 2312

Specifications

Key differences

In depth

Switch with one string

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