💰钛媒体•Stalecollected in 3h
MiniMax Valuation Plummets 65% Amid AI Market Correction
💡A 65% valuation drop for a major AI player is a red flag for the current state of the AI investment bubble.
⚡ 30-Second TL;DR
What Changed
MiniMax experienced a 65% drop in valuation within six months.
Why It Matters
This correction may lead to tighter funding environments for AI startups, forcing a shift from 'growth at all costs' to 'demonstrable revenue models'.
What To Do Next
Focus on building products with clear, immediate ROI and sustainable unit economics to insulate your startup from market volatility.
Who should care:Founders & Product Leaders
Key Points
- •MiniMax experienced a 65% drop in valuation within six months.
- •The market is showing signs of skepticism toward high-growth AI startup valuations.
- •The rapid loss of value reflects broader concerns about AI bubble risks in the capital market.
🧠 Deep Insight
Web-grounded analysis with 18 cited sources.
🔑 Enhanced Key Takeaways
- •MiniMax's valuation peaked at an estimated HK$416 billion before experiencing a 65% decline, resulting in a current market capitalization of approximately HK$145.7 billion as of June 2026.
- •The broader AI market is facing significant investor skepticism, with a May 2026 survey revealing that 67% of investors are concerned about an AI bubble or market correction, driven by factors such as rising AI operational costs and execution risks.
- •MiniMax, which listed on the Hong Kong Stock Exchange in January 2026, reported a total revenue of $79.038 million for 2025 and an adjusted net loss of $251 million, despite its B2B API business showing rapid growth with 69% gross margins.
- •The company's annualized revenue reached an estimated $300 million in May 2026, doubling in just two months, primarily fueled by strong traction in its enterprise API services.
- •Intensified competition among Chinese AI companies has led to industry-wide price compression, with token costs falling significantly, which could further challenge MiniMax's path to profitability amidst ongoing investment in compute infrastructure.
📊 Competitor Analysis▸ Show
| Feature/Model | MiniMax M3 (June 2026) | MiniMax M2 (Oct 2025) | Moonshot AI Kimi K2 Thinking (Nov 2025) | Zhipu AI GLM-4.6 (Jan 2026) | DeepSeek (April 2026) |
|---|---|---|---|---|---|
| Architecture | MSA (MiniMax Sparse Attention), Multimodal | Mixture-of-Experts (MoE) | - | General Language Model (GLM) | - |
| Parameters | - | 230B total, ~10B active | - | 358B total, 32B activated | - |
| Context Window | 1M tokens | 204,000 tokens (input), ~131K tokens (output) | Long context | - | Long context |
| Key Capabilities | Frontier coding, agentic work, multimodal (image/video input, desktop operation) | Coding, agentic tasks, reasoning, office tasks | Reasoning, long context, deep research workflows | Coding specialist, general knowledge, math, law, medicine | Reasoning, long context |
| Benchmarks | SWE-Bench Pro: 59.0%, Terminal-Bench 2.1: 66.0% | LiveCodeBench: ~83% (on par with GLM-4.6), AIME 2025: 78% | Outperformed GPT-5, Claude Sonnet 4.5 on some benchmarks | LiveCodeBench: ~83% (on par with MiniMax-M2), AIME 2025: mid-90s | - |
| API Pricing (per 1M tokens) | Input: $0.30, Output: $1.20 (promotional) | Input: $0.15, Output: $1.20 (M2.5) | - | - | Token costs falling to $0.02 (industry-wide) |
🛠️ Technical Deep Dive
- MiniMax M2: Utilizes a Mixture-of-Experts (MoE) architecture with 230 billion total parameters, but only activates approximately 10 billion parameters per inference pass, optimizing for efficiency, lower latency, and higher throughput in AI agent workflows.
- MiniMax M2.7: Incorporates a recursive self-optimization framework, allowing the model to generate its own evaluation data, identify capability gaps, and produce synthetic training examples, leading to reported performance improvements of about 30% on internal benchmarks.
- MiniMax-01: A hybrid MoE model featuring 456 billion total parameters and around 45.9 billion active parameters, combining linear "Lightning Attention" for extended context processing with standard softmax attention for local precision.
- MiniMax M3: Employs a novel attention architecture called MSA (MiniMax Sparse Attention) and supports ultra-long context windows of up to 1 million tokens. It is natively multimodal, capable of processing image and video input, and can operate a desktop computer.
- Product Offerings: MiniMax develops consumer applications like Talkie (an AI character app, known as Xing Ye in China) and Hailuo AI (a multimodal platform for video, text, and music generation, including audio functions), alongside its MiniMax Agent for enterprise solutions.
🔮 Future ImplicationsAI analysis grounded in cited sources
MiniMax will prioritize profitability and diversified revenue streams beyond consumer applications.
The recent market correction and investor skepticism, coupled with MiniMax's reported adjusted net loss despite revenue growth, will likely compel the company to focus on sustainable financial performance, potentially expanding its B2B API services and agent deployments.
The intense competition within the Chinese AI market will accelerate the development of more efficient and specialized models.
With multiple 'AI Tigers' such as MiniMax, Zhipu AI, and Moonshot AI vying for market share, there will be continuous pressure to innovate in areas like model architecture (e.g., MoE, MSA), context window capabilities, and specialized functionalities (e.g., coding, agentic tasks) to differentiate offerings and reduce operational costs.
MiniMax's valuation will likely remain volatile in the near term due to broader market liquidity shifts and upcoming share lock-up expiries.
The anticipated IPOs of major global AI players like Anthropic and OpenAI are expected to draw liquidity from the market, and MiniMax faces a significant share lock-up expiry (46% of its shares) in early July, which could introduce increased selling pressure.
⏳ Timeline
2021-12
MiniMax founded by former SenseTime researchers.
2022-10
Launched Glow, an AI character app (later rebranded as Talkie/Xing Ye).
2024-03
Alibaba Group led a $600 million financing round, valuing MiniMax at $2.5 billion.
2025-07
Secured nearly $300 million in funding, reaching a post-money valuation of approximately $4 billion.
2025-10
Open-sourced its MiniMax M2 model, designed for coding and agentic tasks.
2026-01-09
Held its Initial Public Offering (IPO) on the Hong Kong Stock Exchange.
2026-03
MiniMax M2.7 model explained, featuring recursive self-optimization capabilities.
2026-06-01
Officially released the MiniMax M3 model, featuring MSA, 1M context, and native multimodality.
📎 Sources (18)
Factual claims are grounded in the sources below. Forward-looking analysis is AI-generated interpretation.
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Original source: 钛媒体 ↗