MiniMax M3 pricing for customer support bot

Quick start

Call MiniMax M3 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-m3",
    max_tokens=1000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.002100 per call at standard rates
# Input:  $0.30/MTok
# Output: $1.20/MTok

How MiniMax M3 compares on cost

Per-call cost for all models scoring 50+ on customer support bot benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.001800/call (14% less, 85/100 quality).

What drives customer support bot cost

Support bots combine RAG's retrieved context with a chatbot's growing history, so they carry both cost curves at once. Volume is high and margins per conversation are thin, which makes the per-call rate matter more than in almost any other use case here. Caching the knowledge base and product context is the single highest-leverage change.

For MiniMax M3 specifically, that means output tokens cost 4.0x more than input, at $1.20 vs $0.30 per MTok. At this use case’s 3,000/1,000 token split, output accounts for 57% of the $0.002100 per-call cost.

MiniMax M3 quality benchmarks for customer support bot

Benchmark data for customer support bot is pending for MiniMax M3. Test against your own evaluation suite before moving to production.

Benchmark data is not yet available for MiniMax M3. We recommend testing against your own evaluation criteria.

About MiniMax M3

Prices from platform.minimax.io/docs/pricing/overview (read 2026-10-11). Long context (>512K tokens) is billed above the listed input and output rates. Cache hit: $0.06/MTok input. No batch discount published. Not yet benchmarked, so never recommended.

Other models from MiniMax

You can compare MiniMax M3 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