AI 模型情报

MiniMax-01

minimax/01

出品方: MiniMax · 系列: minimax · 发布 2025-01-15 · 知识截止: 2024-03-31

$0.139
输入 / 1M token
$1.12
输出 / 1M token
1.00M
上下文长度
1.00M
最大输出

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

能力清单

工具调用推理结构化输出附件开放权重温度可调
支持模态: 输入 text, image · 输出 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.

Coding23
  • Tool calling0/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)20/20
  • Provider availability3/10
Agents18
  • Tool calling0/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit15/15
  • Provider availability3/10
JSON / structured output27
  • Structured output / JSON mode0/50
  • Tool calling0/20
  • Temperature control10/10
  • Price-friendly for high-volume17/20
Cost efficiency60
  • Headline price (log-scaled)60/95
  • Has prompt-cache pricing0/5
Long context90
  • Context window (100K → 2M)80/90
  • Has published price for full window10/10
Vision93
  • Accepts image input50/50
  • Context window (10K → 1M)30/30
  • Has published price10/10
  • Provider availability3/10
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
$1.26
< $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
$2.52
< $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
$0.84
< $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
$2.24
< $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
$2.35
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定价详情

推荐定价来自 nano-gpt · minimax/minimax-01

$0.139
输入
$1.12
输出

在 3 家渠道可用

服务商服务商模型 ID输入 / 1M输出 / 1M上下文发布日期
OpenRouter
openrouter
minimax/minimax-01$0.200$1.101.00M2025-01-15
Kilo Gateway
kilo
minimax/minimax-01$0.200$1.101.00M2025-01-15
NanoGPT
nano-gpt
minimax/minimax-01$0.139$1.121.00M2025-01-15

各渠道数据存在不一致

  • modalities varies across offerings

各服务商对此模型的报告值存在差异。上方「核心数据」使用代表性服务商的值;逐项请以下表为准。

Frequently asked questions

How much does MiniMax-01 cost?

MiniMax-01 costs $0.139 per 1M input tokens and $1.12 per 1M output tokens, sourced from nano-gpt. 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-01?

MiniMax-01 has a context window of 1.00M tokens, with a max output of 1.00M tokens per reply. This is the total combined size of prompt + completion.

Does MiniMax-01 support tool calling?

No. MiniMax-01 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.

Does MiniMax-01 support structured output / JSON mode?

No. MiniMax-01 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-01 accept image input?

Yes. MiniMax-01 accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check MiniMax's docs for the exact rule.

Is MiniMax-01 open-weight?

Yes. MiniMax-01'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-01?

If MiniMax-01 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

最近更新:

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