# LLM.txt - MiniMax M2.5: The $0.15 Open-Weight Model That's Making Claude Opus Look Like a Luxury Purchase ## Article Metadata - **Title**: MiniMax M2.5: The $0.15 Open-Weight Model That's Making Claude Opus Look Like a Luxury Purchase - **URL**: https://llmrumors.com/news/minimax-m25-cheapest-frontier-model - **Publication Date**: February 12, 2026 - **Reading Time**: 15 min read - **Tags**: MiniMax, M2.5, Open-Weight AI, Hailuo AI, Chinese AI, AI Pricing, SWE-bench, Agentic AI - **Slug**: minimax-m25-cheapest-frontier-model ## Summary MiniMax just dropped M2.5, an open-weight model with 230B parameters but only 10B active, that scores within 0.6 points of Claude Opus 4.6 on SWE-bench while costing 20x less. Backed by a fresh Hong Kong IPO and 200M+ users, this isn't another Chinese lab paper. It's the model that makes frontier AI economics work for everyone. ## Key Topics - MiniMax - M2.5 - Open-Weight AI - Hailuo AI - Chinese AI - AI Pricing - SWE-bench - Agentic AI ## Content Structure This article from LLM Rumors covers: - Legal analysis and implications - Industry comparison and competitive analysis - Data acquisition and training methodologies - Financial analysis and cost breakdown - Comprehensive source documentation and references ## Full Content Preview TL;DR: MiniMax released M2.5 on February 12, 2026, an open-weight coding and agentic model that scores 80.2% on SWE-bench Verified (within 0.6 points of Claude Opus 4.6) while charging just $0.15 per million input tokens, 33x cheaper than Opus[1]. The company IPO'd in Hong Kong a month ago at an $11.5B valuation, shares have since quadrupled, and 30% of all tasks at MiniMax HQ are now completed by their own model[2]. This is the first open-weight model to genuinely match Claude Sonnet-tier performance, and it rewrites the economics of AI development. The Chinese AI labs have been releasing models at a pace that makes Western product cycles look leisurely, but MiniMax M2.5 is different. It's not incrementally better. It represents a structural break in what open-weight models can achieve, particularly for the agentic coding workflows that are driving the largest share of enterprise AI spend in 2026. While ByteDance was grabbing headlines with Seedance 2.0 video clips and DeepSeek was teasing V4, MiniMax quietly published benchmark results that made the entire open-source community stop and recalibrate. An open-weight model matching the coding performance of the most expensive frontier models at one-twentieth the cost isn't a minor optimization. It's the kind of shift that forces enterprise procurement teams to rewrite their AI budgets. MiniMax M2.5 dropped during the Chinese Spring Festival AI blitz of February 2026, exactly one year after the DeepSeek R1 shock. But while DeepSeek proved Chinese labs could match Western reasoning capabilities, M2.5 proves they can match Western agentic coding capabilities, the single highest-value commercial AI use case, at a fraction of the price[1]. The OpenHands evaluation team ranked it the #4 model overall, the first open-weight model to ever exceed Claude Sonnet on their composite benchmark[3]. The Numbers That Matter: M2.5 By the Benchmarks Let's be clear about what MiniMax achieved. This isn't a model that trades well on cherry-picked evaluations. The SWE-bench Verified score of 80.2% puts M2.5 within striking distance of Claude Opus 4.6 (80.8%), a model that costs $5.00 per million input tokens versus M2.5's $0.15[1][4]. What's often overlooked is the Multi-SWE-Bench result. At 51.3%, M2.5 holds the #1 position globally on the multi-language coding benchmark, not just among open-weight models but among all models period[1]. The tool-calling score of 76.8% on BFCL outperforms Claude Opus 4.6, Claude Sonnet 4.5, and Gemini 3 Pro. For agentic workflows that depend on reliable function calling, this isn't a marginal difference. Architecture: 230 Billion Parameters, 10 Billion Active The uncomfortable truth about why M2.5 is so cheap is also the reason it's so good. MiniMax built on a Mixture-of-Experts architecture with 230 billion total parameters but only 10 billion active per inference pass[5]. This sparse activation means you get the knowledge capacity of a massive model with the compute costs of a much smaller one. The model was trained using MiniMax's proprietary CISPO algorithm (Clipping Importance Sampling Policy Optimization), first introduced in their M1 paper[5]. What makes M2.5's training unique is the Forge Reinforcement Learning framework: rather than training on synthetic benchmarks, MiniMax trained across 200,000+ real-world environments, actual codebases, web browsers, and office applications[1]. Here's the genius of this approach. Traditional benchmark training optimizes for benchmark performance. Forge RL optimizes for the messy, unpredictable environments where AI agents actually need to work. That's why M2.5's BrowseComp score (76.3%) is so strong... [Content continues - full article available at source URL] ## Citation Format **APA Style**: LLM Rumors. (2026). MiniMax M2.5: The $0.15 Open-Weight Model That's Making Claude Opus Look Like a Luxury Purchase. Retrieved from https://llmrumors.com/news/minimax-m25-cheapest-frontier-model **Chicago Style**: LLM Rumors. "MiniMax M2.5: The $0.15 Open-Weight Model That's Making Claude Opus Look Like a Luxury Purchase." Accessed February 15, 2026. https://llmrumors.com/news/minimax-m25-cheapest-frontier-model. ## Machine-Readable Tags #LLMRumors #AI #Technology #MiniMax #M2.5 #Open-WeightAI #HailuoAI #ChineseAI #AIPricing #SWE-bench #AgenticAI ## Content Analysis - **Word Count**: ~1,340 - **Article Type**: News Analysis - **Source Reliability**: High (Original Reporting) - **Technical Depth**: High - **Target Audience**: AI Professionals, Researchers, Industry Observers ## Related Context This article is part of LLM Rumors' coverage of AI industry developments, focusing on data practices, legal implications, and technological advances in large language models. --- Generated automatically for LLM consumption Last updated: 2026-02-15T00:21:19.820Z Source: LLM Rumors (https://llmrumors.com/news/minimax-m25-cheapest-frontier-model)