MiniMax M2.1

minimax/minimax-m2.1

Run MiniMax M2.1 in a hosted Python Task with extended thinking and file inputs.

MiniMax's M2.1 model via OpenRouter. Consistently ranks in top-10 across benchmarks with strong performance in reasoning and coding tasks. Features 196K context window.

What MiniMax M2.1 supports in qbash

Extended thinkingReasons through a problem before it replies.
Document inputReads PDF, TEXT, DOC, XLS, RTF and 7 more files.
Prompt cachingRepeated input is billed at the cached rate.

What is qbash?

qbash is where you build Tasks: Python programs that run a business process on managed infrastructure. Your code runs the steps and calls a model like MiniMax M2.1 only at the ones that need judgment, with integrations, memory and files available in the same script.

A developer writes the Task once, and anyone on the team runs it from a form, on a schedule, from a webhook or from chat. Each Task is versioned and every run is logged.

How Tasks work

Specifications

Context window: 197Ktokens
Max output: 8,192tokens
Temperature: 0 to 1default 1

Use MiniMax M2.1 in a Python Task

qbash.ai.raw calls MiniMax M2.1 from a Task and returns its reply as a string.

main.py
notes = qbash.inputs.get("notes")

summary = qbash.ai.raw(
    f"Summarize these meeting notes in five bullets:\n\n{notes}",
    model="minimax/minimax-m2.1",
    system="You are a concise analyst.",
)

qbash.output({"summary": summary})

Model calls in Tasks

Extended thinking with MiniMax M2.1

Turn on Thinking in the same Settings popover to have MiniMax M2.1 reason through a problem before it replies.

MiniMax M2.1 pricing

Input	$0.30 per 1M tokens
Output	$1.20 per 1M tokens
Cached input	$0.03 per 1M tokens

Standard rates in USD.

Supported file formats

Documents

PDF
TEXT
DOC
XLS
RTF
DOCX
XLSX
PPTX
PPT
ODT
ODP
ODS