James Ding
March 14, 2025 04:21
Together, the AI introduces dedicated termination criteria with prices up to 43% lower, offering improved GPU inference capacities for scaling AI applications, offering high performance and saving.
Together, AI announced the launch of its new ending points dedicated to demand, designed to provide price performance superior to GPU inference tasks. This development aims to take up the challenges encountered by startups to balance flexibility and affordability in scaling AI applications AI set.
Improved performance and control
The dedicated termination points provide a single resistance to ensure that user traffic is not affected by other users, offering the same high performance as server -free solutions. The offer includes substantial cost savings, complete equipment control and deployment configuration, supporting personalized refined models and no minimum commitment. Users can deploy models such as Deepseek-R1 and Llama 3.3 70B without incurring download or storage costs.
Unrivaled cost savings
With a price reduction of up to 43%, together, the dedicated termination criteria of AI are positioned as the most profitable dedicated GPU inference solution. The price structure offers significant savings compared to other suppliers, with reductions of up to 50% in some cases. This initiative is part of the AI strategy together to provide competitive prices alongside a wide selection of GPU architectures.
Scalability and flexibility
The dedicated termination points allow companies to manage the point of use transparently thanks to vertical and horizontal scaling options. Users can evolve vertically by increasing the number of GPUs or horizontally by adjusting the number of aftershocks to manage cutting -edge workloads. This guarantees coherent performance and optimized costs, which makes it suitable for mission critical AI applications that require reliable QP and predictable availability.
Deployment options
Together, AI now offers a full set of deployment options, including dedicated termination points without server, and monthly reserved deployments. Each option offers different advantages, and users can choose according to their specific flexibility, performance and profitability needs. The dedicated termination criteria are particularly advantageous for customers with strict confidentiality requirements and those who need a deployment of personalized models.
In conclusion, together, the AI dedicated termination criteria offer a versatile and profitable solution for AI companies that seek to evolve their applications while maintaining high performance and control over their deployments.
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