NeevCloud vs. Compute with Hivenet

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Hivenet is a European cloud platform specializing in AI, featuring its proprietary GPU infrastructure located in France, the UAE, and the US. It provides a comprehensive suite of services for AI development teams, including on-demand RTX 5090 GPUs starting at €0.75 per hour, enterprise-grade RTX Pro 6000 for heavy workloads, vCPU instances, S3-compatible object storage, and an Inference API that is compatible with OpenAI. The pricing structure is transparent, charged per second using prepaid credits, without any egress fees or long-term contracts. Users can easily set up their services through the console within minutes or fully automate processes using the public Compute API. With team organization capabilities that enable role-based access, Hivenet is designed for businesses, not just individual users. It serves as a reliable alternative to larger hyperscalers for teams seeking predictable pricing and for European organizations preferring to keep their AI workloads within the EU.

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You can optimize open models such as Llama, Mistral, Qwen, and Gemma using RTX 5090 GPUs starting at €0.75 per hour, with billing calculated by the second. Each card offers 32 GB of VRAM, allowing for LoRA and QLoRA fine-tuning on most models ranging from 7B to 13B on a single GPU. For larger projects, you can utilize multi-GPU setups with up to 8 GPUs. The per-second billing structure ensures that brief experiments and hyperparameter tuning only incur costs for the duration they are active. Begin with PyTorch or Jupyter templates integrated with Hugging Face tools, enabling you to save your environment as an image for easy relaunching in future sessions. Datasets and checkpoints can be stored in S3-compatible object storage without incurring any egress fees. Once your model is trained, you can deploy it on the same platform using vLLM or through a dedicated OpenAI-compatible Inference API endpoint.

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There are two options for executing inference on Hivenet. The first is a self-managed approach where you can deploy RTX 5090 instances starting at €0.75 per hour using the vLLM template, allowing you to host your own models with billing calculated per second. The second option is managed through the Inference API, which provides a dedicated endpoint compatible with OpenAI. This allows for a seamless transition of existing code by simply updating the base URL, eliminating the need to manage the serving infrastructure. The RTX 5090 features 32 GB of GDDR7 and an impressive 1.79 TB/s memory bandwidth, making it an excellent choice for serving models ranging from 7B to 14B parameters, as well as larger quantized models. For bigger models and sustained high utilization, the RTX Pro 6000 is available. Additionally, there are no egress fees, meaning you won’t incur costs for the responses sent to users. Hivenet offers regions in France, the UAE, and the US to ensure low latency and compliance with EU data residency requirements.

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Hivenet Compute provides a comprehensive GPU and CPU infrastructure, fully managed by Hivenet, with facilities located in France, the UAE, and the USA. Teams can access on-demand RTX 5090 GPUs equipped with 32 GB GDDR7 starting at €0.75 per hour, as well as RTX Pro 6000 GPUs for more intensive production tasks. Additionally, virtual CPU (vCPU) instances are available, ranging from 2 to 32 vCPUs. Billing operates on a per-second basis using prepaid credits, ensuring no long-term commitments or egress fees. Surrounding the compute instances are essential resources for AI teams, including S3-compatible object storage, an OpenAI-compatible Inference API for dedicated model endpoints, and a public Compute API with a comprehensive OpenAPI specification. Team structures are organized with role-based access for optimal collaboration. For projects that require compliance with European regulations, workloads can be processed in the French region. This infrastructure is particularly advantageous for startups, research labs, and product teams seeking production capabilities without the high costs, quotas, or vendor lock-in associated with hyperscalers.

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Utilize cutting-edge RTX 5090 GPUs (featuring 32 GB of GDDR7 and 5th-generation Tensor Cores) starting at just €0.75 per hour. Scale your setup with up to 8 GPUs per instance, enjoying per-second billing that ensures you're only charged for active time. This service is ideal for applications in computer vision, small to medium language models, diffusion models, and experimental prototypes, where a cluster of H100s would be excessive. For projects requiring more memory capacity, the RTX Pro 6000 is also an option. Get started quickly with ready-to-use templates for PyTorch, Jupyter, and Docker, allowing you to begin training within minutes and easily save and relaunch your environment exactly as it was. Store your datasets and checkpoints in S3-compatible object storage without any egress fees for data transfer. You can also automate your runs via the public Compute API. Our research collaborators and clients include institutions such as INRIA, Proteineer, and the University of Arizona, with services available in regions across France, the UAE, and the US.

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Rent RTX 5090 GPUs starting at just €0.75 per hour, charged by the second, and stop incurring costs as soon as the instance is terminated. Each RTX 5090 is equipped with 32 GB of GDDR7 memory and offers an impressive bandwidth of 1.79 TB/s, making it ideal for various tasks such as inference, fine-tuning, and image generation, without the need to overpay for unnecessary data-center cards. You can scale your usage from 1 to 8 GPUs per instance, or upgrade to the RTX Pro 6000 for handling larger models and ongoing production demands. Easily launch from pre-built templates designed for PyTorch, Jupyter, vLLM, ComfyUI, and Docker, save your custom images, and access via SSH. Enjoy no egress fees and flexible, short-term contracts. Our services are available in France, the UAE, and the US, ensuring you can keep your data within the EU when required.

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