KI‑Modell‑Intelligenz

MiniMax M2.5

amazon-bedrock/minimax-m2-5

Von amazon-bedrock · Familie: minimax · veröffentlicht 2026-03-18

⚠ Dies ist ein Community-Finetune oder Derivat — keine offizielle Anbieter-Veröffentlichung.

$0.300
Eingabe / 1 Mio. Tokens
$1.20
Ausgabe / 1 Mio. Tokens
197K
Kontextfenster
98K
Max. Ausgabe

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

Fähigkeiten

Tool CallingReasoningStrukturierte AusgabeAnhängeOffene GewichteTemperatur-Steuerung
Modalitäten: Eingabe text · Ausgabe 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.

Coding57
  • Tool calling40/40
  • Structured output0/20
  • Reasoning10/10
  • Context window (100K → 1M)6/20
  • Provider availability1/10
Agents66
  • Tool calling35/35
  • Structured output0/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output47
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume17/20
Cost efficiency58
  • Headline price (log-scaled)58/95
  • Has prompt-cache pricing0/5
Long context55
  • Context window (100K → 2M)45/90
  • Has published price for full window10/10
Production-readiness50
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)0/15

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
$2.10
< $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
$4.20
< $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
$1.20
< $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
$3.60
< $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
$4.32
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

Preis-Details

Empfohlene Preise von amazon-bedrock · minimax.minimax-m2.5

$0.300
Eingabe
$1.20
Ausgabe

Bei 1 Anbietern verfügbar

AnbieterAnbieter-Modell-IDEingabe / 1MAusgabe / 1MKontextVeröffentlicht
Amazon Bedrock
amazon-bedrock
minimax.minimax-m2.5$0.300$1.20197K2026-03-18

Frequently asked questions

How much does MiniMax M2.5 cost?

MiniMax M2.5 costs $0.300 per 1M input tokens and $1.20 per 1M output tokens, sourced from amazon-bedrock. 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 M2.5?

MiniMax M2.5 has a context window of 197K tokens, with a max output of 98K tokens per reply. This is the total combined size of prompt + completion.

Does MiniMax M2.5 support tool calling?

Yes. MiniMax M2.5 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 M2.5 support structured output / JSON mode?

No. MiniMax M2.5 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 M2.5 accept image input?

No. MiniMax M2.5 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is MiniMax M2.5 open-weight?

Yes. MiniMax M2.5'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 M2.5?

If MiniMax M2.5 doesn't fit, consider Palmyra X5, Nova Pro, Nova Micro. 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.

More amazon-bedrock models

Capability lists this model is in

Zuletzt aktualisiert:

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.