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    Building the Infrastructure for Production AI: Fireworks AI + GMI Cloud

    2026年6月02日

    Fireworks AI, the frontier training and inference platform powering production AI applications for companies like Uber, Genspark, and Shopify, selected GMI Cloud to support scalable, production-ready open-model inference for developers and enterprises. 

    Fireworks AI is a NVIDIA-backed training and inference platform, and GMI Cloud is an inaugural NVIDIA Reference Platform Cloud Partner. 

    Together, this collaboration reflects a shared commitment to scaling high-performance, production-ready AI infrastructure for the next generation of developers and enterprises.

    As AI adoption accelerates, teams are moving beyond experimentation and into production environments that require faster inference, reliable infrastructure, and scalable GPU capacity. Open models are becoming a critical part of this shift, giving builders more flexibility, control, and cost efficiency. However, deploying these models at scale requires both optimized inference platforms and a strong infrastructure layer. 

    For production workloads, performance is measured not only by model quality, but by latency, reliability, throughput, and the ability to efficiently serve millions of requests across distributed environments.

    WHY THIS COLLABORATION MATTERS

    The collaboration between Fireworks AI and GMI Cloud reflects a broader industry shift: AI builders increasingly need both powerful inference platforms and reliable cloud infrastructure to move from prototype to production. By combining Fireworks AI’s inference expertise with GMI Cloud’s high-performance AI infrastructure, the partnership supports faster deployment, stronger workload scalability, and a more flexible foundation for building with open models.

    THE INFRASTRUCTURE REQUIREMENTS OF PRODUCTION AI

    The next generation of AI applications is moving beyond simple chat interfaces toward systems that reason, use tools, process multimodal inputs, and operate continuously in production environments. These workloads place new demands on infrastructure that extend far beyond raw GPU capacity.


    Production AI requires high-throughput, low-latency inference to support real-time user experiences, as well as the ability to deploy and scale large open models across text, image, audio, video, and agentic workflows. As organizations adopt increasingly sophisticated AI systems, infrastructure must also support long-context reasoning, secure multi-tenant environments, dynamic workload scaling, and efficient orchestration that maximizes GPU utilization while reducing inference costs.

    By combining Fireworks AI's optimized inference platform with GMI Cloud's high-performance AI infrastructure, developers and enterprises gain a foundation designed to meet the operational requirements of production-scale AI.

    FUTURE OF COMPUTE CAPACITY WITH FLEXIBLE, RELIABLE, FASTER PRODUCTION 

    Together, the companies enable developers and enterprises to move from experimentation to production faster, with the flexibility, reliability, and compute capacity required to support the next generation of AI applications.

    GMI Team

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