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Meituan: LongCat 2.0 vs Perceptron: Perceptron Mk1

A side-by-side comparison of Meituan: LongCat 2.0 ($1.05 / 1M tokens) and Perceptron: Perceptron Mk1 ($0.52 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Meituan: LongCat 2.0	Perceptron: Perceptron Mk1
Provider	Meituan	Perceptron
Input	$1.05 / 1M tokens	$0.52 / 1M tokens
Output	$4.20 / 1M tokens	$5.25 / 1M tokens
Cache read	$0.02 / 1M tokens	-
Context window	1,048,756	32,768
Max output	262,144	8,192
Input	text	text, image, video
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Jul 20, 2026	May 12, 2026

Key differences

Perceptron: Perceptron Mk1 is 50% cheaper on input tokens.
Meituan: LongCat 2.0 is 20% cheaper on output tokens.
Meituan: LongCat 2.0 reads 32.0× more context (1,048,756 tokens).
Only Meituan: LongCat 2.0 supports tool calling.
Only Perceptron: Perceptron Mk1 supports structured JSON output.
A request with 1,000 input and 500 output tokens costs $0.00315 with Meituan: LongCat 2.0 and $0.00315 with Perceptron: Perceptron Mk1.

In depth

Meituan: LongCat 2.0 is a text model from Meituan, released on 2026-07-20. Perceptron: Perceptron Mk1 is a text model from Perceptron, released on 2026-05-12. Both are served on api14 as chat models with text output, so at the surface level they look interchangeable, but the details of what each accepts and how much it can hold at once push them toward different jobs.

The clearest split is context and input types. LongCat 2.0 accepts text only and carries a context window of 1,048,756 tokens, which is far larger than the 32,768 tokens Perceptron Mk1 supports. Perceptron Mk1, in exchange, accepts images and video alongside text, so it can look at visual input while LongCat 2.0 cannot. On tooling, LongCat 2.0 is the one that exposes tool calling through tool_choice and tools, while Perceptron Mk1 is the one that exposes structured outputs. Both list reasoning and include_reasoning, so neither has a meaningful edge there. LongCat 2.0 also exposes a wider parameter set overall, including logit_bias, min_p, repetition_penalty, seed and stop, while Perceptron Mk1 keeps a smaller set. On price, Perceptron Mk1 is the cheaper option for input, and LongCat 2.0 is the cheaper option for output, so the cost picture depends on how much you send versus how much you generate.

For practical work, reach for LongCat 2.0 when the job is text in and text out and the material is large: long documents, big codebases, extended transcripts, or anything where you would otherwise have to chunk and stitch. It is also the pick when you need the model to call tools, since that is where its parameter list goes further. Reach for Perceptron Mk1 when the input is not purely text, such as screenshots, diagrams, photos or short video clips that need to be described, summarized or reasoned over, and when you want the reply to come back in a strict structured shape. Its smaller context means you should keep those requests tight, and its cheaper input pricing suits workloads that push a lot of material in relative to what comes back out.

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 key, and use the chat completions shape you already use. The only thing that changes between the two is the model id: use "meituan/longcat-2.0" for LongCat 2.0 and "perceptron/perceptron-mk1" for Perceptron Mk1. Everything else, the messages array, the streaming flag and the response parsing, stays as it is, so you can switch models by editing one string or by routing on a config value.

There are cases where the other model is still the better pick even after that. If your task is text only but you want structured outputs, Perceptron Mk1 is the one that supports them, so it can be the right call despite the smaller window. If your task involves images or video, LongCat 2.0 cannot take them at all, so Perceptron Mk1 is the only option of the two. And if output volume dominates your usage, LongCat 2.0 is the cheaper side for output, which can matter more than input pricing on generation heavy jobs.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "meituan/longcat-2.0" to "perceptron/perceptron-mk1" and prompts, streaming and tools keep working.

Meituan: LongCat 2.0 details & playground →Perceptron: Perceptron Mk1 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": "perceptron/perceptron-mk1",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

More comparisons

LongCat 2.0 vs Perceptron Mk1: API price, context & features · api14