MiniMax M2 pricing for code refactoring

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: ~$0.005040 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 code refactoring benchmarks. Hover for details.

Highest-quality affordable option: Claude Haiku 4.5 at $0.0240/call (4.8x the cost, 72/100 quality). MiniMax M2 is already the cheapest choice for code refactoring.

What drives code refactoring cost

Refactoring sends existing code and gets a rewritten version back, so input and output are roughly symmetric, unusual for a code task. That symmetry means neither rate dominates and total cost tracks the size of the file. The practical lever is scope: refactoring one module per call rather than a whole package keeps you off the long-context pricing tier, where some providers re-rate the entire request.

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 4,000/4,000 token split, output accounts for 79% of the $0.005040 per-call cost.

MiniMax M2 quality benchmarks for code refactoring

Benchmark data for code refactoring 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