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Model Evolution

See how MiniMax's models evolved by answering the same challenge across generations.

We compare AI models for a living. On purpose. We chose this.

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MiniMax

MiniMax

Chinese AI research company behind the MiniMax family, focusing on long-context reasoning and efficient MoE architectures.

Total Models

7

Text Models

6

Image Models

1

Active Period

Mar 2025 – Feb 2026

Chinese AI research company focused on generative AI.

Long-context reasoning with efficient MoE architectures.

Active in both text and image generation domains.

Compare MiniMax Models

MiniMax M2.5

Feb 2026

MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1 to extend into general office work, reaching fluency in generating and operating Word, Excel, and Powerpoint files, context switching between diverse software environments, and working across different agent and human teams. Scoring 80.2% on SWE-Bench Verified, 51.3% on Multi-SWE-Bench, and 76.3% on BrowseComp, M2.5 is also more token efficient than previous generations, having been trained to optimize its actions and output through planning.

conversationreasoningcode-generationanalysisagentic-tool-useplanningdata-extraction

MiniMax M2-her

Jan 2026

MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent in tone and personality, it supports rich message roles and can learn from example dialogue to better match the style and pacing of your scenario.

conversationreasoning

MiniMax: MiniMax M2.1

Dec 2025

MiniMax: MiniMax M2.1 model integrated via automation on 2025-12-23

conversationreasoningcode-generationanalysis

MiniMax M2

Oct 2025

MiniMax M2 is a high-efficiency 10B activated parameter model optimized for coding agents, compile-run-fix loops, and long-horizon reasoning. It balances responsiveness with strong SWE-Bench and Terminal-Bench results, excels at code generation, planning, and tool use, and preserves reasoning continuity across multi-step tasks.

conversationreasoningcode-generationanalysisplanningagentic-tool-usetool-use

MiniMax M1

Jun 2025

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 to process long sequences (up to 1 million tokens) while maintaining competitive FLOP efficiency. With 456 billion total parameters and 45.9B active per token, this variant is optimized for complex, multi-step reasoning tasks.

conversationreasoningcode-generationanalysisagentic-tool-usememory

MiniMax Image-01

Jun 2025

MiniMax's first image generation model with character reference support for consistent character generation across multiple images. Produces high-quality, detailed images with strong compositional abilities.

image-generation

MiniMax Speech-02 HD

Mar 2025

High-definition text-to-speech with studio-quality output and fine-grained emotion control.

text-to-speechaudio-generation