MiniMax M1
minimax/m1От MiniMax · семейство: minimax · выпуск 2025-01-08
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Возможности
Model fit scores
0–100 · higher is betterThese 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 output17
- Structured output / JSON mode0/50
- Tool calling0/20
- Temperature control0/10
- Price-friendly for high-volume17/20
Cost efficiency59
- Headline price (log-scaled)59/95
- Has prompt-cache pricing0/5
Long context90
- Context window (100K → 2M)80/90
- Has published price for full window10/10
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.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $1.29 < $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 | $2.57 < $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 | $0.89 < $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 | $2.31 < $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 | $2.34 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Детализация цен
Рекомендованная цена от 302ai · MiniMax-M1
Доступна у 3 провайдеров
| Провайдер | ID модели провайдера | Вход / 1M | Выход / 1M | Контекст | Выпуск |
|---|---|---|---|---|---|
| NanoGPT nano-gpt | MiniMax-M1 | $0.139 | $1.33 | 1M | 2025-01-08 |
| 302.AI 302ai | MiniMax-M1 | $0.132 | $1.25 | 1M | 2025-06-16 |
| Qiniu qiniu-ai | MiniMax-M1 | $0.580 | $2.32 | 1M | 2025-06-17 |
Расхождения данных между провайдерами
- release_date varies (span 160d): 2025-01-08, 2025-06-16, 2025-06-17
Провайдеры сообщают разные значения для этой модели. Сводка выше использует репрезентативного провайдера; детали — в таблице.
Frequently asked questions
How much does MiniMax M1 cost?
MiniMax M1 costs $0.132 per 1M input tokens and $1.25 per 1M output tokens, sourced from 302ai. 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 M1?
MiniMax M1 has a context window of 1M tokens, with a max output of 131K tokens per reply. This is the total combined size of prompt + completion.
Does MiniMax M1 support tool calling?
No. MiniMax M1 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does MiniMax M1 support structured output / JSON mode?
No. MiniMax M1 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 M1 accept image input?
No. MiniMax M1 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is MiniMax M1 open-weight?
Yes. MiniMax M1'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 M1?
If MiniMax M1 doesn't fit, consider MiniMax-M3, MiniMax-M2.7, MiniMax-M2.5. 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.
Explore more
More MiniMax models
- MiniMax-M3$0.30 in / $1.20 out
- MiniMax-M2.7$0.30 in / $1.20 out
- MiniMax-M2.5$0.30 in / $1.20 out
- MiniMax-M3.1-Flash$0.15 in / $0.60 out
- MiniMax-M2.1$0.30 in / $1.20 out
Capability lists this model is in
Последнее обновление:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.