minimax-m2.1
novita/m2-1提供： novita · ファミリー: minimax · リリース 2025-12-26
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
機能一覧
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.
Coding58
- Tool calling40/40
- Structured output0/20
- Reasoning10/10
- Context window (100K → 1M)6/20
- Provider availability2/10
Agents67
- Tool calling35/35
- Structured output0/25
- Reasoning15/15
- Output token limit15/15
- Provider availability2/10
JSON / structured output37
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control0/10
- Price-friendly for high-volume17/20
Cost efficiency63
- Headline price (log-scaled)58/95
- Has prompt-cache pricing5/5
Long context56
- Context window (100K → 2M)46/90
- Has published price for full window10/10
Production-readiness68
- Number of independent providers10/40
- 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 | $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. |
料金詳細
推奨料金 (提供元): llmgateway-providers · novita/minimax-m2.1
2 か所で利用可能
| プロバイダー | プロバイダーモデルID | 入力 / 1M | 出力 / 1M | コンテキスト | リリース日 |
|---|---|---|---|---|---|
| Poe poe | novita/minimax-m2.1 | Unknown | Unknown | 205K | 2025-12-26 |
| LLM Gateway llmgateway-providers | novita/minimax-m2.1 | $0.300 | $1.20 | 205K | 2025-12-23 |
プロバイダー間でデータに差異
- context_window varies: 204800, 205000
プロバイダーごとに本モデルの値が異なります。上部の「主要数値」は代表的プロバイダーを使用しています。詳細は表をご確認ください。
Frequently asked questions
How much does minimax-m2.1 cost?
minimax-m2.1 costs $0.300 per 1M input tokens and $1.20 per 1M output tokens, sourced from llmgateway-providers. 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-m2.1?
minimax-m2.1 has a context window of 205K tokens, with a max output of 131K tokens per reply. This is the total combined size of prompt + completion.
Does minimax-m2.1 support tool calling?
Yes. minimax-m2.1 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-m2.1 support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for minimax-m2.1 in our data source. Verify with novita's official documentation before relying on it in production.
Can minimax-m2.1 accept image input?
No. minimax-m2.1 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is minimax-m2.1 open-weight?
No. minimax-m2.1 is a proprietary model — only novita (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to minimax-m2.1?
If minimax-m2.1 doesn't fit, consider glm-4.6v, GLM-4.6, GLM-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
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Capability lists this model is in
最終更新：
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.