MiniMax: MiniMax M1
MiniMax • LLM
MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...
Specifications
Context Window
1.0M tokens
Input Price/1M
$0.40
Output Price/1M
$2.20
Parameters
—
Max Output
40K tokens
Information
- Tool Calling
- ✅ Supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: MiniMax: MiniMax M1
What is MiniMax: MiniMax M1?
MiniMax: MiniMax M1 is an AI model developed by MiniMax, classified as a large language model (LLM). It focuses on text processing and natural language generation. As a proprietary model, it is available via MiniMax's cloud API. With a context window of 1.0M tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
MiniMax: MiniMax M1 is usage-based, priced at $0.4/1M input tokens and $2.2/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Benchmarks & Performance
We don't have detailed benchmark results for MiniMax: MiniMax M1 yet. Benchmarks are updated weekly as new data becomes available from sources like Artificial Analysis, LM Arena, and LiveBench.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
MiniMax: MiniMax M1 is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), automation with tool calling (API integration, databases, external systems), high-volume chatbots and automated support, complex reasoning, math problem solving, and logical analysis, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, MiniMax: MiniMax M1 competes directly with similarly capable models. MiniMax competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is MiniMax: MiniMax M1?
MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...
How much does MiniMax: MiniMax M1 cost?
MiniMax: MiniMax M1 costs $0.4/1M input tokens and $2.2/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does MiniMax: MiniMax M1 compare with other models?
We don't have detailed benchmarks for MiniMax: MiniMax M1 yet. Check the main benchmark page to compare available models.
Is MiniMax: MiniMax M1 open source?
No, MiniMax: MiniMax M1 is a proprietary model from MiniMax. It is available via cloud API. For open source alternatives, check our open source model ranking.
What is MiniMax: MiniMax M1 best for?
MiniMax: MiniMax M1 excels at complex reasoning and problem solving. With its large context window, it handles long documents, codebases, and extended conversations. It supports tool calling for API integrations and automation.
Last updated: May 24, 2026 • View methodology →