AI 모델 인텔리전스

MiniMax-M2.7-highspeed

minimax/m2-7-highspeed

제공: MiniMax · 패밀리: minimax · 출시 2026-03-18 · 지식 컷오프: 2025-01-01

$0.600
입력 / 1M 토큰
$2.40
출력 / 1M 토큰
205K
컨텍스트 창
131K
최대 출력

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

기능

✓ 도구 호출✓ 추론? 구조화 출력✗ 첨부✓ 오픈 웨이트✓ 온도 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.

Coding64
  • Tool calling40/40
  • Structured output0/20
  • Reasoning10/10
  • Context window (100K → 1M)6/20
  • Provider availability8/10
Agents73
  • Tool calling35/35
  • Structured output0/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability8/10
JSON / structured output44
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume14/20
Cost efficiency56
  • Headline price (log-scaled)51/95
  • Has prompt-cache pricing5/5
Long context56
  • Context window (100K → 2M)46/90
  • Has published price for full window10/10
Production-readiness98
  • Number of independent providers40/40
  • 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
$4.20
< $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
$8.40
< $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
$2.40
< $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
$7.20
< $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
$8.64
< $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: minimax · MiniMax-M2.7-highspeed

$0.600
입력
$2.40
출력
$0.060
캐시 읽기
$0.375
캐시 쓰기

가장 저렴한 제공자: minimax-coding-plan · Unknown 입력 + Unknown 출력

8곳 제공사에서 이용 가능

제공자제공자 모델 ID입력 / 1M출력 / 1M컨텍스트출시일
MiniMax (minimax.io)
minimax
MiniMax-M2.7-highspeed$0.600$2.40205K2026-03-18
MiniMax Coding Plan (minimax.io)
minimax-coding-plan
MiniMax-M2.7-highspeedUnknownUnknown205K2026-03-18
MiniMax Coding Plan (minimaxi.com)
minimax-cn-coding-plan
MiniMax-M2.7-highspeedUnknownUnknown205K2026-03-18
MiniMax (minimaxi.com)
minimax-cn
MiniMax-M2.7-highspeed$0.600$2.40205K2026-03-18
Vercel AI Gateway
vercel
minimax/minimax-m2.7-highspeed$0.600$2.40205K2026-03-18
302.AI
302ai
MiniMax-M2.7-highspeed$0.600$4.80205K2026-03-19
ZenMux
zenmux
minimax/minimax-m2.7-highspeed$0.611$2.44205K2026-03-20
LLM Gateway
llmgateway
minimax-m2.7-highspeed$0.600$2.40205K2026-03-18

제공자 간 데이터 불일치

  • modalities varies across offerings

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

Frequently asked questions

How much does MiniMax-M2.7-highspeed cost?

MiniMax-M2.7-highspeed costs $0.600 per 1M input tokens and $2.40 per 1M output tokens, sourced from minimax. 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-M2.7-highspeed?

MiniMax-M2.7-highspeed has a context window of 205K tokens, with a max output of 131K tokens per reply. This is the total combined size of prompt + completion.

Does MiniMax-M2.7-highspeed support tool calling?

Yes. MiniMax-M2.7-highspeed supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does MiniMax-M2.7-highspeed support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for MiniMax-M2.7-highspeed in our data source. Verify with MiniMax's official documentation before relying on it in production.

Can MiniMax-M2.7-highspeed accept image input?

No. MiniMax-M2.7-highspeed only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is MiniMax-M2.7-highspeed open-weight?

Yes. MiniMax-M2.7-highspeed's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.

What are the best alternatives to MiniMax-M2.7-highspeed?

If MiniMax-M2.7-highspeed doesn't fit, consider MiniMax-M2.5, MiniMax-M2.1, MiniMax-M2.7. 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 come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

Explore more

More MiniMax models

Capability lists this model is in

See also

마지막 업데이트:

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.