MiniMax M2.7 — API Pricing & Benchmarks

MiniMax M2.7 is MiniMax's mid reasoning model. The API costs $0.30 per 1M input tokens and $1.20 per 1M output tokens ($0.52 blended at a 3:1 ratio), with cached input at $0.06. On the independently measured Artificial Analysis Intelligence Index it scores 38.9, ranking #44 of 68 models tracked on this site, with a median output speed of 50 tokens/sec.

Explore provider routes and additional benchmark sources for MiniMax M2.7

ProviderMiniMax
Input price / 1M tokens$0.30
Output price / 1M tokens$1.20
Cached input / 1M tokens$0.06
Blended price (3:1)$0.52
Context window
Max output tokens131K
Knowledge cutoff
Licenseopen weights
Input modalitiesT
Output speed (tok/s)50
Released
Artificial Analysis Intelligence Index38.9
LMArena Elo1405
GPQA Diamond87.4%
Humanity's Last Exam29.6%

Where MiniMax M2.7 fits

On a blended 3:1 basis MiniMax M2.7 costs $0.52 per 1M tokens, cheaper than 79% of the 80 priced models in this index. It sits in the mid-tier bracket where most production chat, RAG and summarization workloads run: meaningfully cheaper than flagships while keeping most of their capability. Measured output speed of 50 tokens/sec is below the index median of 104 — typical of reasoning-heavy models, and worth checking against interactive latency budgets. The weights are open, so it can be self-hosted for data-residency or cost reasons instead of consumed via API. Cached input is priced at $0.06 (80% below standard input), which rewards prompt structures with long stable prefixes — see our caching guide.

Price history

PeriodInput $/1MOutput $/1MCached $/1M
2026-07-18 → current$0.30$1.20$0.06

No list-price changes recorded since tracking began. Full dataset: price-history.json (CC BY 4.0).

Alternatives at a similar price

About MiniMax

MiniMax ships open-weights M-series models that undercut most of the market: its flagship M3 costs less than many providers' small models while posting mid-tier benchmark scores.

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