AI 모델 인텔리전스

MiniMax M2-her

minimax/m2-her

제공: MiniMax · 패밀리: minimax · 출시 2026-01-23

$0.300
입력 / 1M 토큰
$1.20
출력 / 1M 토큰
66K
컨텍스트 창
2K
최대 출력

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

기능

도구 호출추론구조화 출력첨부오픈 웨이트온도 제어
모달리티: 입력 text · 출력 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding3
  • Tool calling0/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)0/20
  • Provider availability3/10
Agents3
  • Tool calling0/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit0/15
  • Provider availability3/10
JSON / structured output27
  • Structured output / JSON mode0/50
  • Tool calling0/20
  • Temperature control10/10
  • Price-friendly for high-volume17/20
Cost efficiency63
  • Headline price (log-scaled)58/95
  • Has prompt-cache pricing5/5
Long context0
  • Context ≥ 100K0/100
Production-readiness73
  • Number of independent providers15/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers8/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$2.10
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$4.20
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$1.20
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$3.60
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$4.32
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

가격 상세

추천 가격 제공자: openrouter · minimax/minimax-m2-her

$0.300
입력
$1.20
출력
$0.030
캐시 읽기

3곳 제공사에서 이용 가능

제공자제공자 모델 ID입력 / 1M출력 / 1M컨텍스트출시일
OpenRouter
openrouter
minimax/minimax-m2-her$0.300$1.2066K2026-01-23
NanoGPT
nano-gpt
minimax/minimax-m2-her$0.302$1.2166K2026-01-24
Kilo Gateway
kilo
minimax/minimax-m2-her$0.300$1.2066K2026-01-23

제공자 간 데이터 불일치

  • context_window varies: 65532, 65536

제공자별로 이 모델의 값이 다릅니다. 위의 핵심 정보는 대표 제공자 기준이며, 제공자별 상세는 표를 참고하세요.

Frequently asked questions

How much does MiniMax M2-her cost?

MiniMax M2-her costs $0.300 per 1M input tokens and $1.20 per 1M output tokens, sourced from openrouter. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of MiniMax M2-her?

MiniMax M2-her has a context window of 66K tokens, with a max output of 2K tokens per reply. This is the total combined size of prompt + completion.

Does MiniMax M2-her support tool calling?

No. MiniMax M2-her does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.

Does MiniMax M2-her support structured output / JSON mode?

No. MiniMax M2-her does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.

Can MiniMax M2-her accept image input?

No. MiniMax M2-her only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is MiniMax M2-her open-weight?

No. MiniMax M2-her is a proprietary model — only MiniMax (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to MiniMax M2-her?

If MiniMax M2-her doesn't fit, consider MiniMax-M2.5, MiniMax-M2.7, MiniMax-M2.1. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

More MiniMax models

마지막 업데이트:

Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.