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Ling 3.1 Flash vs Ministral 3 8B 2512: API price, context & features · api14

inclusionAI: Ling 3.1 Flash vs Mistral: Ministral 3 8B 2512

A side-by-side comparison of inclusionAI: Ling 3.1 Flash ($0.16 / 1M tokens) and Mistral: Ministral 3 8B 2512 ($0.52 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	inclusionAI: Ling 3.1 Flash	Mistral: Ministral 3 8B 2512
Provider	inclusionAI	Mistral
Input	$0.16 / 1M tokens	$0.52 / 1M tokens
Output	$0.47 / 1M tokens	$0.52 / 1M tokens
Cache read	$0.03 / 1M tokens	$0.05 / 1M tokens
Context window	1,000,000	262,144
Max output	262,144	209,715
Input	text	text, image
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Oct 2, 2026	Dec 2, 2025

Key differences

inclusionAI: Ling 3.1 Flash is 70% cheaper on input tokens.
inclusionAI: Ling 3.1 Flash is 10% cheaper on output tokens.
inclusionAI: Ling 3.1 Flash reads 3.8× more context (1,000,000 tokens).
Only inclusionAI: Ling 3.1 Flash supports reasoning effort control.
A request with 1,000 input and 500 output tokens costs $0.000394 with inclusionAI: Ling 3.1 Flash and $0.000788 with Mistral: Ministral 3 8B 2512.

In depth

inclusionAI: Ling 3.1 Flash is a text model from inclusionAI, released in October 2026. Mistral: Ministral 3 8B 2512 is a text model from Mistral, released in December 2025. Both are served as chat style models on api14, and both are aimed at developers who want a general purpose model they can call from an OpenAI compatible client. The main structural difference is that Ling 3.1 Flash is a much larger context model, while Ministral 3 8B 2512 is a smaller model that also accepts images.

On capabilities, Ling 3.1 Flash offers a context window of one million tokens, while Ministral 3 8B 2512 offers 262144 tokens. That makes Ling 3.1 Flash the one to reach for when your prompt or your retrieved context is very long, since you can fit far more material into a single call. Ministral 3 8B 2512 accepts both text and image input, so it is the only one of the two that can look at a picture, while Ling 3.1 Flash takes text only. Ling 3.1 Flash also exposes reasoning related parameters that Ministral 3 8B 2512 does not, which matters if you want to control or inspect a reasoning step. Both support tool calling and structured outputs, so neither has an edge there. Ling 3.1 Flash is the cheaper option on input, while Ministral 3 8B 2512 is the cheaper option on output, so the cost picture depends on whether your workload is input heavy or output heavy. Check the live price table for the actual numbers.

For practical choices, pick Ling 3.1 Flash when you are feeding in long documents, large codebases, or long conversation histories, and when you want the extra reasoning controls or a lower input cost. Pick Ministral 3 8B 2512 when your task involves images alongside text, when your output is long and you want the lower output cost, or when a 262144 token window is already more than enough for the job. If your prompts are short and your responses are long, the output side of the bill will dominate, which favors Ministral 3 8B 2512. If your prompts are long and your responses are short, the input side dominates, which favors Ling 3.1 Flash.

Calling either model through api14 works the same way, because the API is OpenAI compatible. You point your existing client at the api14 base URL, send your request to the chat completions endpoint, and set the model field to the id you want. The only change between the two is that string: use inclusionai/ling-3.1-flash for Ling 3.1 Flash, or mistralai/ministral-8b-2512 for Ministral 3 8B 2512. Your messages, tools, and response format fields carry over unchanged, so switching models is a one line edit rather than a rewrite.

There are still cases where the other model wins. If you need image input, Ling 3.1 Flash cannot help you, so Ministral 3 8B 2512 is the only option of the two. If you need a very large context window or reasoning controls, Ministral 3 8B 2512 cannot match Ling 3.1 Flash, so the choice goes the other way. Match the model to the shape of your request, not to a general sense of which one is stronger.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "inclusionai/ling-3.1-flash" to "mistralai/ministral-8b-2512" and prompts, streaming and tools keep working.

inclusionAI: Ling 3.1 Flash details & playground →Mistral: Ministral 3 8B 2512 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.chat.completions.create({
  "model": "mistralai/ministral-8b-2512",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

inclusionAI: Ling 3.1 Flash vs Mistral: Ministral 3 8B 2512

Specifications

Key differences

In depth

Switch with one string

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