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MiniMax M2.7 Highspeed

minimax-m2.7-highspeed

Text generation for writing, questions and summaries. Try the verified short-copy example.

Pricing
Input 0.875001 · Output 3.500004 USD / 1M tokens
Output
Chat
Added to catalog
Oct 28, 2026
Input
Examples
*

Enter a message or import TXT / Markdown text. Available attachment formats are shown below.

Default: Chinese cafe copy example
Default: 1024

Estimate the cost first. Generation starts only after confirmation.

OutputFill example
<think>The user is asking: "为一家名为 Orux Café 的社区咖啡店写两句温暖的开业文案,包含欢迎邻居带书来阅读。不超过80字。" This is Chinese. The user wants two warm opening slogans for a community cafe named Orux Café, include invitation for neighbors to bring books to read, and total length should be no more than 80 characters (Chinese characters count). So we need to produce exactly two sentences (or two lines) that are warm and inviting, mention the cafe name, and ask neighbors to bring books. The total characters (including punctuation) must be ≤ 80 Chinese characters. We should be careful to count characters. Chinese characters each count as one character (including punctuation?). Typically Chinese characters are counted individually, punctuation also counts as a character. So we need to ensure ≤80 characters total. Two lines combined. We can produce something like: "欢迎来到 Orux Café,温暖的咖啡与书香相伴,欢迎邻居携一本好书,一起分享阅读时光。" But that's a single line. The requirement: "两句温暖的开业文案". Means two sentences, or two lines? It says "两句". That's likely two sentences. Each sentence can be separate lines. We need to keep them under 80 characters total (including punctuation). Let's design. Potential sentences: 1. "Orux Café 温暖开业,咖啡香浓,笑声盈盈,欢迎邻居带上心爱的书,一起在书香中品味生活。" (That is quite long. Let's count characters.) We'll count characters manually. First, we need to know the length limit: "不超过80字" means less than or equal to 80 Chinese characters. The phrase "字" can be considered as characters, not words. So we need to ensure ≤80 characters. We'll need to count carefully. First draft sentence 1: "Orux Café 温暖开业,咖啡香浓,笑声盈盈,欢迎邻居带上心爱的书,一起在书香中品味生活。" Count characters: We need to treat each Chinese character (including punctuation like ,, 。) as a character. Latin letters "Orux Café" are each considered characters, perhaps each letter counts as a character, but for simplicity we count them as characters anyway. Let's count: "O" (1), "r" (2), "u" (3), "x" (4), " " (space?) Possibly not counted? Chinese spaces might not be counted; but we can avoid spaces. We'll write "OruxCafé" without spaces. But "Café" includes "C", "a", "f", "é". For simplicity, we count each Latin letter as a character. But it's safer to keep the text mostly Chinese characters and minimize Latin characters. We'll produce two sentences in Chinese but include the name "Orux Café" which includes spaces maybe. But we can use "Orux Café" as is, with a space. Let's produce two sentences: Sentence 1: "Orux Café 温暖开业,咖啡香浓,笑声盈盈,欢迎邻居带上心爱的书,一起在书香中品味生活。" Sentence 2: "在这里,书页轻翻,咖啡轻抿,邻里情深,共享阅读的温暖时光。" Now count characters for each. Sentence 1: Let's write exactly: "Orux Café 温暖开业,咖啡香浓,笑声盈盈,欢迎邻居带上心爱的书,一起在书香中品味生活。" Counting characters: 1 O 2 r 3 u 4 x 5 (space) – do we count spaces? Usually Chinese text does not have spaces. We'll remove the space between "Orux" and "Café" maybe. So we can write "OruxCafé". But the user gave "Orux Café". However, we can remove spaces to save characters. But the limit is generous (80 characters). Let's count with a space: it counts as a character. But we can avoid spaces to keep length short. Better to not include spaces: "OruxCafé". That would be a single token. So we have "OruxCafé". Characters: O, r, u, x, C, a, f, é = 8 characters. Now after that we have a space before "温暖". Typically there would be a space, but we can avoid space. We can just attach "温暖开业". So "OruxCafé温暖开业". That continues directly. That means "O" (1), "r" (2), "u" (3), "x" (4), "C" (5), "a" (6), "f" (7), "é" (8), "温" (9), "暖" (10), "开" (11), "业" (12). So far 12 characters. Now we have ",". That's punctuation (count 1). So char 13. Then "咖啡香浓". "咖</think>

README

Text generation for writing, questions and summaries. Try the verified short-copy example.

Model capabilities

Input modalities
Text
Output modalities
Text
Context caching
Supported
Tool calling
Not confirmed
Streaming
Not confirmed
Batch inference
Not supported

API protocol support

Chat Completions
Supported
Responses
Not supported
Gemini
Not supported
Anthropic
Not supported

Model limits

Context length
Not confirmed
Maximum output
Not confirmed

Writing, questions and summaries

The Chinese cafe opening copy is a real response from this model. Edit its prompt or select a summary or coding prompt. The latter examples provide reusable inputs without fabricated outputs.

Pricing and usage

Input, output and cache usage are billed separately according to the price table. Context and time-based tiers apply where listed; peak and off-peak times use UTC+8. Review the estimate before calling; final cost depends on returned usage.

Text requests and responses have been verified. Refer to the capabilities section for other input types and tools.

Parameters

Fields accepted in the request body for this model.

messagesmessages
Required

Enter a message or import TXT / Markdown text. Available attachment formats are shown below.

max_tokensinteger
Optional
Range: ≥ 1Default: 1024
Advanced
temperaturenumber
Optional

Adjust response randomness. Tune either temperature or top_p.

Range: 0 – 2
top_pnumber
Optional
Range: 0 – 1
response_formatobject
Optional

For JSON output, describe the expected JSON structure in your prompt.

Values: Text / JSON object
toolsobject
Optional
tool_choiceobject
Optional

Select a function, for example {"type":"function","function":{"name":"lookup"}}.

Pricing

Pricing

USD / 1M tokens

Standard

Input0.875001
Output3.500004
Cache read0.087501
Cache write (5 min)0.546876

Bill actual quantity

Minimum per call: 0 USD · Rounding is applied once to the total cost

Only listed usage types are supported for automatic billing

Pricing follows the selected specifications

Prices are billed per unit consumed with no monthly minimum. See billing guide for USD estimates and actual usage charges.

POST https://orux.top/api/v1/chat/completions

Frequently asked questions

About MiniMax M2.7 Highspeed pricing, capabilities and API access on Orux AI.

Does selecting an example incur a charge?

No. Selecting an example only fills the form. A model call starts after you confirm generation or send a request.

What is MiniMax M2.7 Highspeed?

MiniMax M2.7 Highspeed: Text generation for writing, questions and summaries. Try the verified short-copy example.

How much does MiniMax M2.7 Highspeed cost on Orux AI?

Input: 175.0002 Credits; output: 700.0008 Credits, per 1M tokens. See the pricing section on this page for MiniMax M2.7 Highspeed pricing and applicable conditions. Charges depend on the selected parameters and recorded usage.

What inputs and outputs does MiniMax M2.7 Highspeed support?

MiniMax M2.7 Highspeed accepts Text and returns Text.

Where can I access the MiniMax M2.7 Highspeed API?

Create an Orux AI API key and send an authenticated POST request to https://orux.top/api/v1/chat/completions, using minimax-m2.7-highspeed as the model identifier. Try the playground on this page and use the API example for the exact request format.