MiniMax M2 pricing for data extraction

Quick start

Call MiniMax M2 with the OpenAI Python SDK pointed at api.minimax.chat:

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.minimax.chat/v1",
    api_key=os.environ["MINIMAX_API_KEY"],
)
response = client.chat.completions.create(
    model="minimax-m2",
    max_tokens=1000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.002040 per call at standard rates
# Input:  $0.26/MTok
# Output: $1.00/MTok

How MiniMax M2 compares on cost

Per-call cost for all models scoring 50+ on data extraction benchmarks. Hover for details.

Highest-quality affordable option: Gemini 3 Flash at $0.005000/call (2.5x the cost, 86/100 quality). MiniMax M2 is already the cheapest choice for data extraction.

What drives data extraction cost

Extraction is input-heavy and output-light (the raw document goes in, structured fields come out), which makes it one of the cheapest tasks per unit of value on this list. Output is small enough that output pricing is nearly irrelevant. Cost tracks document size, so the lever is sending only the pages that contain the fields you want.

For MiniMax M2 specifically, that means output tokens cost 3.8x more than input, at $1.00 vs $0.26 per MTok. At this use case’s 4,000/1,000 token split, output accounts for 49% of the $0.002040 per-call cost.

MiniMax M2 quality benchmarks for data extraction

Benchmark data for data extraction is pending for MiniMax M2. Test against your own evaluation suite before moving to production.

Benchmark data is not yet available for MiniMax M2. We recommend testing against your own evaluation criteria.

About MiniMax M2

Prices from platform.minimax.io/docs/pricing/overview (read 2026-10-11). No cache discount published (set 1.0 — no discount). No batch discount published. Not yet benchmarked, so never recommended.

Other models from MiniMax

You can compare MiniMax M2 head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions