Inteligencia de modelos de IA

MiniMax M1

minimax/m1

Por MiniMax · familia: minimax · lanzado 2025-06-16

$0.132
Entrada / 1M tokens
$1.25
Salida / 1M tokens
1M
Ventana de contexto
40K
Salida máxima

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

Capacidades

✓ Llamada a herramientas✓ Razonamiento? Salida estructurada✗ Adjuntos✓ Pesos abiertos✓ Control de temperatura
Modalidades: entrada text · salida 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.

Coding75
  • Tool calling40/40
  • Structured output0/20
  • Reasoning10/10
  • Context window (100K → 1M)20/20
  • Provider availability5/10
Agents70
  • Tool calling35/35
  • Structured output0/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability5/10
JSON / structured output47
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • 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-readiness83
  • Number of independent providers25/40
  • 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
$1.29
< $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.

Detalle de precios

Precio recomendado de 302ai · MiniMax-M1

$0.132
Entrada
$1.25
Salida

Disponible en 5 proveedores

ProveedorID de modelo del proveedorEntrada / 1MSalida / 1MContextoLanzado
OpenRouter
openrouter
minimax/minimax-m1$0.400$2.201M2025-06-17
302.AI
302ai
MiniMax-M1$0.132$1.251M2025-06-16
NanoGPT
nano-gpt
MiniMax-M1$0.139$1.331M2025-06-16
Qiniu
qiniu-ai
MiniMax-M1UnknownUnknown1M2025-08-05
Kilo Gateway
kilo
minimax/minimax-m1$0.400$2.201M2025-06-17

Inconsistencias de datos entre proveedores

  • release_date varies (span 50d): 2025-06-16, 2025-06-17, 2025-08-05

Los proveedores reportan valores distintos para este modelo. Los datos clave de arriba usan un proveedor representativo; consulta la tabla para detalles por proveedor.

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 40K tokens per reply. This is the total combined size of prompt + completion.

Does MiniMax M1 support tool calling?

Yes. MiniMax M1 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 M1 support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for MiniMax M1 in our data source. Verify with MiniMax's official documentation before relying on it in production.

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-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

Última actualización:

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.