MiniMax M2-her
VerifiedA closed-source LLM built for extended text processing and analysis.
About MiniMax M2-her
MiniMax M2-her uses a transformer-based design optimized for long sequences. Its 65536-token context enables coherent handling of lengthy documents and multi-turn dialogues. The model remains fully closed-source with no public weights or architecture details released.
Key strengths center on stable performance across extended text inputs without requiring local deployment. MiniMax maintains control over updates and infrastructure to ensure consistent output quality. This setup suits organizations that prefer managed API access over self-hosted solutions.
Common applications include document summarization, content generation, and conversational interfaces. Developers integrate it via MiniMax APIs for tasks that benefit from large context retention. It serves professional workflows where proprietary safeguards and reliability matter most.
Capabilities
How MiniMax M2-her compares
MiniMax M2-her (striped bar) vs other language models on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · MiniMax M2-her ranks #23 of 34
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Long-form document summarization
MiniMax M2-her processes entire books or research papers up to 65k tokens in a single pass, producing coherent summaries that preserve key arguments and citations.
Extended multi-turn coding assistance
The model maintains context across lengthy codebases and debugging sessions, suggesting consistent refactors without losing track of earlier requirements.
Detailed technical report generation
Users can supply comprehensive specifications and data tables within the 65k-token window to receive structured, citation-aware technical documents.
Strengths & limitations
Strengths
- +Large 64k token context window
- +Pure text modality efficiency
- +Suitable for long documents or dialogues
Limitations
- –Text-only, no multimodal support
- –Standard LLM hallucination risks
- –No specialized domain fine-tuning mentioned
Cost calculator
Estimate what MiniMax M2-her would cost for your usage.
Based on MiniMax M2-her's $0.30/1M input · $1.20/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "minimax/minimax-m2-her",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: minimax/minimax-m2-her
Editor's verdict
MiniMax M2-her is MiniMax's proprietary language models with a 66K-token context window.
At $1.20 per 1M output tokens, it is mid-priced for its class.
It is available through MiniMax's API and aggregators like OpenRouter.
Best suited to large 64k token context window and pure text modality efficiency.
Frequently asked questions
The model supports a context length of 65536 tokens, allowing it to handle large documents or extended conversations in one request.
User reviews
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