MiniMax M2 pricing for legal analysis

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=4000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.006600 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 legal analysis benchmarks. Hover for details.

Highest-quality affordable option: GPT 5.6 Luna at $0.006800/call (1.0x the cost, 86/100 quality). MiniMax M2 is already the cheapest choice for legal analysis.

What drives legal analysis cost

Legal work is heavy on both sides: long source documents in, detailed analysis out. It is also the case where accuracy is worth the most, so the cheapest-viable-model logic that works for classification does not apply. Long contracts frequently cross long-context pricing thresholds, which can re-rate the entire request rather than just the excess.

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 10,000/4,000 token split, output accounts for 61% of the $0.006600 per-call cost.

MiniMax M2 quality benchmarks for legal analysis

Benchmark data for legal analysis 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