Morgan Stanley initiated coverage on MiniMax, giving it an &#34;Overweight&#34; rating and a target price of HKD 930, positioning it as a &#34;global leader in AI foundational models.&#34; In this report, Morgan Stanley's real bet is not on short-term profits, but on two main lines: whether the model's capabilities stand in the global top tier, and whether the revenue structure has the flexibility for global expansion.
According to the Wind Trading Desk, Morgan Stanley analyst Gary Yu, who is responsible for the coverage, believes that MiniMax has entered the global SOTA model camp, with well-developed multimodal capabilities and a highly scalable commercialization path. Based on this, the company's revenue is expected to grow from USD 75 million in 2025 to USD 700 million in 2027, achieving a 9-10 times increase over two years. Once a generational advantage in technical capabilities is formed, the revenue curve will show a &#34;stair-step&#34; leap.
The report's explanation for the high valuation is also very straightforward: This is an asset where &#34;technology determines the revenue ceiling, and globalization determines the valuation system.&#34; If model performance continues to enter the global top tier, its ceiling comes from the global TAM; if the revenue structure is primarily overseas, the valuation anchor will naturally align with international comparable companies.
<h2>Technical Capability as the Starting Point for Valuation</h2>
Morgan Stanley attributes MiniMax's core competitiveness to three points: continuous iteration capability, multimodal layout, and cost efficiency.
In independent benchmark tests, MiniMax-M2 ranked fifth in the global LLM leaderboard upon release; the latest flagship model MiniMax-M2.5 ranks sixth and fourth among open-source models. As of mid-February 2026, M2.5 ranked first in token usage on OpenRouter, reaching 19.7 trillion tokens, with a market share of 58.8% in programming scenarios.
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These data indicate that the model has entered high-frequency real-world calling scenarios, rather than remaining in laboratory scoring.
More critically, the cost structure. The company employs MoE architecture and Linear Attention mechanisms, with Model Flop Utilization exceeding 75% during the inference phase, higher than the industry average of 40%-50%. Inference efficiency directly affects API pricing and gross margin elasticity, determining whether profit margins can improve in tandem with scale expansion.
Morgan Stanley expects the company's gross margin to increase from 12% in 2024 to 32% in 2027. However, operating losses during the same period are expected to widen, with a projected non-IFRS operating loss of approximately USD 484 million in 2027. This is not a logic of profit inflection point, but a path of &#34;first expanding technology and scale, then looking at profits.&#34;
Technical leadership does not guarantee profitability, but it determines the revenue ceiling
<h2>Revenue Structure Determines Growth Slope</h2>
MiniMax's business model is not driven by a single product, but rather operates on three parallel lines:
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2C: Agent and companion products Talkie/Xingye
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2P: Hailuo AI, MiniMax Audio
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2B: Open Platform API
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As of the first nine months of 2025, the company's MAU grew from 3.1 million in 2023 to 27.6 million, with 1.77 million paying users. The revenue structure is becoming more diversified, with the Open Platform's share continuously increasing.
Morgan Stanley expects the Open Platform's revenue share to rise from 29% in 2024 to 40% in 2027, with a three-year compound growth rate exceeding 200%. After breakthroughs in model capabilities, demand for enterprise APIs is more likely to experience &#34;leapfrog&#34; growth.
The report emphasizes an industry characteristic: the growth of foundational model companies is often triggered by key generational models, rather than a smooth climb. OpenAI's ChatGPT 3.5 and Anthropic's Claude 3.5 Sonnet both brought revenue leaps after model upgrades.
Whether MiniMax will replicate this rhythm depends on the next-generation model launched in mid-2026.
<h2>Globalization is a Prerequisite for Valuation</h2>
Morgan Stanley particularly emphasizes MiniMax's &#34;Born Global&#34; path.
The share of overseas revenue has increased from 19% in 2023 to 73% in the first nine months of 2025. The regional distribution is: Asia-Pacific 61%, Americas 24%, EMEA 15%.
Against the backdrop of the global foundational model market size expected to grow from USD 10.7 billion in 2024 to USD 20.65 billion in 2029 (CAGR 80.7%), the company's current global market share is only about 0.3%. As long as the share increases slightly, revenue elasticity will become apparent.
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More importantly, the valuation system. If revenue primarily comes from overseas markets, and customers mainly rely on APIs and subscriptions, its valuation logic is closer to that of international AI comparable companies, rather than traditional Chinese software companies.
This is also the core basis for Morgan Stanley's 54 times 2027 P/S.
<h2>Valuation Discrepancies Focused on &#34;Next-Generation Model&#34;</h2>
The three scenario assumptions are very clear:
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Base case: USD 700 million revenue in 2027, corresponding to 54 times P/S, target price HKD 930.
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Optimistic case: USD 1 billion revenue in 2027, target price HKD 1240.
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Pessimistic case: USD 400 million revenue in 2027, target price HKD 300.
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The only variable determining valuation differences is whether the next-generation model launched in mid-2026 reaches or exceeds the global SOTA level
Risks are also focused on: GPU supply and geopolitical restrictions, resource gaps with OpenAI and other large-scale players, price pressures from model commercialization, and ongoing cash consumption.
<h2>This is the pricing of &#34;technology realization capability&#34;</h2>
Morgan Stanley does not shy away from reality: currently, no pure AI foundational model company has achieved stable profitability. MiniMax is expected to have an average monthly cash consumption of about $27.9 million in 2025, with limited visibility on profitability.
But the core judgment of the report is that the competition in the foundational model industry is not about marketing, but about generational breakthroughs. Technological capability determines the revenue ceiling, while the global market determines the valuation anchor point.
If model upgrades lead to non-linear revenue expansion, the current valuation is merely a forward discounting of future scale; if the model fails to secure a position in the global top tier, the valuation will also shrink rapidly.
This is a bet on the rhythm of technology realization. Morgan Stanley chooses to stand on the side of &#34;globally top-tier foundational model scarce assets.&#34;

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If the MiniMax model's performance continues to enter the global top tier, its ceiling comes from the global Total Addressable Market (TAM); if the revenue structure is primarily overseas, the valuation anchor will naturally align with international comparable companies, benchmarking against non-traditional Chinese software companies

- Morgan Stanley initiates coverage of MiniMax with an "Overweight" rating and a target price of 930 HKD, positioning it as a global AI foundational model leader.  
- The report highlights MiniMax's advanced model capabilities and scalable commercial pathways, predicting revenue growth from $75 million in 2025 to $700 million by 2027.  
- It emphasizes that while technological leadership sets revenue limits, globalization will drive valuation, with overseas revenue expected to increase significantly as the company's market share in the growing foundational model sector expands.

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MINIMAX-WP

Morgan Stanley evaluates MiniMax as "a globally top-tier foundational model scarce asset," with the core logic of high valuation being "technology determines the ceiling, globalization determines valuation."