MiniMax has officially released its new flagship model M2, aiming to redefine the balance between capability and cost in the large-model race, including innovations from ChatGPT Atlas. Priced at just $0.3 per million input tokens and $1.2 per million output tokens—around 8% of Claude’s cost—M2 delivers near-GPT-5 performance across multiple benchmarks.
によると、 Artificial Analysis leaderboard, M2 ranks Top 5 globally, showing comprehensive reasoning, coding, and agent orchestration power that rivals the best frontier models.
Why M2 Stands Out: From Language to Action
M2 focuses on three directions: code generation, agent orchestration, and deep search — redefining what an AI model can do rather than what it can say.
1. Code Intelligence: From “Writing Code” to “Building Software”
On end-to-end development benchmarks such as Terminal-Bench and SWE-Bench, M2 demonstrates impressive full-cycle capabilities. It doesn’t just generate code — it runs, debugs, verifies, and even fixes it automatically. This enables a complete code–run–test–repair loop, showing behavior closer to an independent developer than a traditional “code-writing model.”
2. Agent Capabilities: From “Answering” to “Doing Work
M2 can plan and execute complex toolchains, coordinating between Shell, browser, Python executors, and various MCP tools. In benchmarks like BrowseComp, it not only retrieves hard-to-find information but also maintains traceability, self-correction, and workflow recovery — key features for real-world agent automation.
3. Multi-Modal DNA: Understanding Sound, Image, and Text Together
One developer reportedly used M2 to automatically build a “Palace Museum” website — the model generated the full page layout, curated exhibition images, and even produced audio guides using its built-in voice model. This demonstrates more than just API calling; it shows true cross-modal collaboration — a “chemical reaction” across text, image, and audio models built within the same ecosystem. When all modalities share a unified foundation, synergy becomes deep integration, not just connection.
4. Deep Search & Reasoning: M2 Approaches ChatGPT-5-Level Performance
M2 ranks #2 globally on the XBench-DeepSearch benchmark, just behind GPT-5, and again #2 on ByteDance’s FinSearchComp-Global for financial information retrieval, trailing only Grok-4. In one reported test, M2 read over 800 academic papers on architecture and real-estate economics, synthesizing 200 key findings into a coherent literature review — roughly twice the coverage of Claude 4.5.
What This Means for Knowledge Work and Personal Agents
While M2 pushes boundaries in code and system-level intelligence, a new generation of AI agents like アイウィーバー is redefining how individuals 使用 such intelligence.
と アイウィーバー, users can instantly analyze documents, summarize PDFs, extract insights, and generate reports — all through personalized AI agents that learn from their own uploaded knowledge.
This marks a convergence:
- M2 represents model-level autonomy — thinking and acting across modalities.
- アイウィーバー represents user-level autonomy — reasoning and producing from personal knowledge.
Together, they outline the future of agent collaboration: AI that not only understands data but also applies it to real work.
📚Use Cases: Where M2 Meets iWeaver
| Workflow | M2 Capability | iWeaver Extension |
|---|---|---|
| Software Development | Multi-file code generation & debugging | AI ドキュメント要約ツール – Auto-generate requirement docs and technical summaries AIライティング – Create structured reports and engineering briefs |
| 市場調査 | Multi-source search & synthesis | AI Summarizer – Extract key insights from online sources AIマインドマップ – Turn research findings into visual knowledge maps |
| Education & Academia | Read hundreds of papers and synthesize insights | 研究論文要約ツール – Summarize academic papers at scale AIクイズジェネレーター – Generate practice questions and study guides |
| Creative Workflows | Multi-modal generation and media curation | AI画像サマライザー – Analyze and summarize visual content Content Idea Generator – Produce creative concepts and titles from summaries |
By integrating both levels — model and personal agent — professionals can achieve a new productivity frontier: from “querying AI” to “collaborating with AI.”
The Bigger Picture: Toward Full-Stack AI Fusion
As MiniMax stated, “The real competition is not who has the strongest model, but who can integrate vision, speech, reasoning, and action into one seamless experience.”
いつ GPT-5, M2, and next-generation AIエージェント converge, AI will shift from a tool to a true collaborator—an extension of human capability.
For professionals, this means:
- Less context switching between tools.
- Instant summarization and decision support.
- Smarter, context-aware assistants that evolve with you.
From Models to Meaningful Work
The launch of MiniMax M2 signals not just a new model war, but a directional war — toward integrated, intelligent ecosystems.
And as these ecosystems expand, platforms like iWeaver will play a crucial role: bridging cutting-edge models with real-world productivity.
💗Get Knowledge Ready. Get Tasks Done. Try アイウィーバー today — your personal AI agent that turns knowledge into action.
