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Chinese AI startup MiniMax has unveiled M3, a powerful large language model that combines top-tier performance with open-source flexibility, all while slashing costs for enterprises.
The landscape of enterprise AI just got a major shake-up. On Sunday evening Eastern time, Chinese AI startup MiniMax released its highly anticipated M3 large language model (LLM). This new entrant is making waves by offering frontier-tier coding and agentic performance, a 1-million-token context window, and native multimodality-all at a fraction of the cost of leading proprietary models like GPT-5.5 and Gemini 3.1 Pro.
MiniMax M3 is available via the MiniMax API at a special discounted price of $0.3 per 1 million input tokens and $1.20 per million output tokens (on fresh cache) for the next week. Even at its full price of $0.6 per million input tokens and $2.40 per million output tokens, M3 remains just 8-20% the cost of leading U.S. Models.
The traditional matrix governing large language model development has long dictated a rigid choice: developers can either access top-tier closed-source intelligence behind restrictive APIs or deploy nimble, cost-effective open models that falter on multi-step reasoning, dense coding tasks, and massive data sequences. MiniMax M3 fundamentally upends this paradigm.
M3's performance on key benchmarks is impressive:

| Model | Input Cost (per 1M tokens) | Output Cost (per 1M tokens) | Total Cost (limited time) | Source | |----------------|-----------------------------|-----------------------------|----------------------------|--------------------------------| | MiMo-V2.5 Flash | $0.10 | $0.30 | $0.40 | Xiaomi MiMo | | deepseek-v4-flash | $0.14 | $0.28 | $0.42 | DeepSeek | | deepseek-v4-pro | $0.435 | $0.87 | $1.305 | DeepSeek | | MiniMax-M3 | $0.30 | $1.20 | $1.50 (limited time) | MiniMax | | Gemini 3.1 Flash-Lite | $0.25 | $1.50 | $1.75 | Google |
To understand how MiniMax M3 achieves such impressive performance and cost efficiency, let's dive into some of its key architectural details:
MiniMax M3 represents a significant leap forward in the world of large language models. By combining top-tier performance with open-source flexibility and cost efficiency, M3 is poised to disrupt the current landscape dominated by proprietary models. Enterprises now have a powerful tool at their disposal that can handle complex tasks while keeping costs under control.
For developers and researchers, the availability of M3's open weights opens up new possibilities for experimentation and customization. The model's performance on key benchmarks and its cost structure make it an attractive option for both small startups and large enterprises looking to leverage AI without breaking the bank.
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MiniMax M3 debuts, eclipsing GPT-5.5 and Gemini 3.1 Pro on key benchmark performance for just 5-10% of the cost
↗ https://venturebeat.com/technology/minimax-m3-debuts-eclipsing-gpt-5-5-and-gemini-3-1-pro-on-key-benchmark-performance-for-just-5-10-of-the-cost
About the author
Kai built ML infrastructure at a Bay Area startup before developing an obsession with transformer architectures and inference optimisation that eventually pulled him out of product work entirely. A stint at a compute research lab sharpened his instinct for what actually matters in a model release versus what is marketing. He writes from the inside — from the perspective of someone who has debugged the systems he is describing at three in the morning. He is allergic to hype and instinctively drawn to the unglamorous plumbing questions that everyone else skips over.
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