代码和视频 火山引擎一个没落下

At the 2026 Summer Yuan Dongli (Original Power) Conference hosted by Volcano Engine, the company launched a number of new production-grade AI products and released the latest growth data for China's large language model (LLM) market. For general users, the key takeaways are:

1. Domestic Chinese LLMs have now reached the top international level in core performance. The newly launched Doubao 2.1 Pro crossed the production-grade threshold in three key domains: coding, intelligent agents, and vision-language processing. It outperforms the international competitor Claude Opus 4.6 on multiple benchmarks, and its API service is already open for integration into most mainstream products for immediate use.

2. It offers a dramatic price advantage: the total cost of using Doubao 2.1 Pro is nearly 80% lower than that of its international competitors. For high-frequency use cases, Doubao 2.1 Turbo cuts prices by an additional 50%, making it affordable for ordinary developers and individual users.

3. A range of new content creation models will launch soon. Seedance 2.5, a video generation model launching in July, can directly output 30-second 4K HD videos, supports multi-source generation and local editing. When paired with Volcano Engine's image and audio generation models, it can meet all types of content creation needs.

The conference outlined the latest development trends of the large model industry, helping brands map out their AI upgrade paths and implement AI applications to cut costs and boost efficiency. Key takeaways for brands include:

1. Clear industry and consumer trends have emerged: LLMs have moved past pure technology competition and entered the stage of large-scale commercialization. Market demand has shifted from casual chatbot use cases to production-grade delivery, with large models gradually expanding from consumer-facing use cases to enterprise and industrial scenarios. Industry-wide demand for AI is growing rapidly: daily token consumption has grown more than 10-fold in one year, and 200 enterprises across the internet, manufacturing, finance, automotive and other sectors now exceed 1 trillion tokens in annual usage. The integration of AI into core business operations is accelerating.

2. Production-grade AI capabilities can support brands' multi-scenario needs. LLM's production-grade coding capabilities help brands quickly build digital business systems, while multimodal generation capabilities allow brands to produce marketing copy, images and videos quickly at low cost. Seedance 2.5 can directly output HD videos that meet marketing requirements, drastically lowering the barrier to content production.

3. Domestic large models offer significant cost advantages, with total usage costs 80% lower than top international models, greatly reducing the financial pressure for brands to adopt AI.

The conference revealed the latest changes in the LLM-as-a-Service (MaaS) market, pointing to new growth opportunities for AI service sellers. Key takeaways are as follows:

1. The market offers enormous growth potential. China's public cloud MaaS market has entered a period of explosive growth, with Volcano Engine ranking first with a 49.5% market share. Industry-wide demand is growing rapidly: daily token usage of Doubao LLM grew more than 10-fold over the past year, and the number of enterprises with annual token usage exceeding 1 trillion doubled in six months to 200. As AI integration into enterprise core business continues to accelerate, sellers focused on AI-enabled production services will see massive growth opportunities.

2. Clear implementation paths are available. Sellers can build businesses around production-grade LLM capabilities, including code development, agent building, content generation, and other related services. Volcano Engine has opened APIs for its full model line and launched supporting development tools, allowing sellers to integrate directly without incurring high in-house R&D costs.

3. The cost advantage of these models helps sellers boost their competitiveness. Since LLMs themselves are priced far lower than international competitors, sellers can serve customers at lower cost to gain a price advantage. In addition, tiered pricing across different product lines covers both high- and low-frequency use cases to meet the needs of different customers.

The production-grade LLM capabilities launched at the conference provide new support for factories advancing digital transformation and implementing AI applications. Key takeaways are as follows:

1. AI capabilities ready for direct deployment in production scenarios are now mature. LLMs have entered the production-grade application phase. The Seedance video generation model is already deployed in industrial manufacturing, providing factories with tools for data synthesis, scenario simulation, and production process demonstration, helping cut R&D and testing costs and improve R&D efficiency. Doubao 2.1 Pro's production-grade coding capability has already completed the full engineering workflow of RTL testing for chip design, enabling it to support industrial software development, complex product R&D and other tasks for factories.

2. The technology opens new business opportunities for factories. A large number of manufacturing enterprises have already integrated LLM services. The maturation of LLM technology allows factories to build brand-new intelligent production models, develop new value-added services, and expand revenue streams.

3. It offers new insights for factories advancing digital transformation. Factories do not need to invest heavily to develop their own LLMs in-house; they can leverage mature MaaS services to implement AI applications quickly, lowering the barrier and risk of transformation and accelerating the pace of digital upgrade.

The conference revealed the latest development trends and technical progress of the large model industry, helping AI service providers align their strategies and solve customer pain points. Key takeaways are as follows:

1. The industry development trajectory is clear: the large model industry has shifted from technology exploration to large-scale commercialization. Customers' core demand has shifted from "can chat" to "can deliver production-grade results", with a growing number of enterprise clients seeking production-grade AI capabilities. Demand is growing rapidly and the market continues to expand, so providers that focus on production-grade AI services will capture industry growth dividends.

2. The latest cutting-edge technical results are available for direct integration. The domestic model Doubao 2.1 Pro has crossed the production-grade threshold in coding, intelligent agents, and multimodal processing, with core performance outperforming top international competitors at 80% lower total cost. Volcano Engine has also built out a full-stack multimodal model lineup covering code, video, image, and audio generation, capable of meeting the diverse needs of enterprise clients across industries.

3. Mature turnkey solutions are available for reuse. Volcano Engine has launched a full suite of production-grade AI solutions, including an upgraded AI-native cloud architecture, Agent development tools, an enterprise-grade Agent workbench, and an enterprise security product system. Service providers can use this framework to quickly build customized AI solutions for clients, drastically cutting their own development costs and improving delivery efficiency.

The conference revealed shifting demand in the enterprise AI service market and the latest operational strategies of leading platforms, providing valuable reference for LLM platform development. Key takeaways are as follows:

1. Market demand has changed clearly: enterprise demand for AI has upgraded from experimental chatbot use cases to production-grade business delivery. Clients now have higher requirements for model stability, long-horizon task processing, and multimodal understanding, alongside strict demands for cost control. Overall market demand is growing rapidly, with more than 1.1 million enterprises and individual users already using LLM services, and demand continues to expand quickly.

2. Mature practices from leading platforms offer clear reference. Volcano Engine built a full-stack LLM portfolio covering multiple scenarios, continuously and rapidly iterates model capabilities to match evolving customer demand, and launched low-barrier development tools to reduce integration friction for developers and enterprises, then captured market share with competitive pricing. It now holds nearly half of China's public cloud MaaS market.

3. Platforms need to avoid common pitfalls. Given the rapid pace of LLM technology iteration and fast-upgrading customer demand, platforms that fail to keep up with technical upgrades and meet production-grade demand will likely be pushed out of the market. Continuous investment in technical iteration is required to keep pace with market changes.

The conference released the latest development data and progress of China's large model industry, offering high reference value for research on LLM industry development. Key insights are as follows:

1. Clear new industry trends have emerged: China's large model industry has completed its transition from technical validation to large-scale commercialization, and the industry's demand structure has undergone a fundamental shift. Where consumer-facing chat and entertainment use cases dominated before, enterprise production-grade delivery demand now makes up the majority of the market. Domestic large models have caught up to top international models in core capabilities, and are now able to compete head-to-head with leading global models.

2. The industry shows new development characteristics. The MaaS model has now been fully validated by the market. Volcano Engine ranks first in China's public cloud MaaS market with a 49.5% share, and industry growth has been extraordinary. Daily token usage of Doubao LLM has grown 1,500x over two years, and more than 10x in the past year alone; the number of enterprises with annual token usage exceeding 1 trillion doubled in six months, confirming that enterprise demand has entered an explosive growth phase.

3. The business model is now proven. The pay-per-token MaaS model has gained broad market acceptance, and differentiated pricing can meet the needs of customers across different scenarios and scales. Low-cost pricing has further accelerated the adoption of AI in enterprise scenarios, providing a valuable new case study for industry research.