Forge the AI frontier. Train on expert-built GPU clusters.
Built by AI researchers for AI innovators, Arvae GPU Clusters are powered by NVIDIA GB200, H200, and H100 GPUs, along with the Arvae Kernel Collection — delivering up to 24% faster training operations.
Top-Tier NVIDIA GPUs
NVIDIA's latest GPUs, like GB200, H200, and H100, for peak AI performance, supporting both training and inference.
Accelerated Software Stack
The Arvae Kernel Collection includes custom CUDA kernels, reducing training times and costs with superior throughput.
High-Speed Interconnects
InfiniBand and NVLink ensure fast communication between GPUs, eliminating bottlenecks and enabling rapid processing of large datasets.
Highly Scalable & Reliable
Deploy 16 to 1000+ GPUs across global locations, with 99.9% uptime SLA.
Expert AI Advisory Services
Arvae AI's expert team offers consulting for custom model development and scalable training best practices.
Robust Management Tools
Slurm and Kubernetes orchestrate dynamic AI workloads, optimizing training and inference seamlessly.
Inference that's fast, simple, and scales as you grow.
Fast
Run leading open-source models like Llama-3 on the fastest inference stack available, up to 4x faster than vLLM.
Outperforms Amazon Bedrock, and Azure AI by over 2x.
Cost-efficient
Arvae Inference is 11x lower cost than GPT-4o when using Llama-3 70B. Our optimizations bring you the best performance at the lowest cost.
Scalable
We obsess over system optimization and scaling so you don't have to. As your application grows, capacity is automatically added to meet your API request volume.
Serverless Endpoints for leading open-source models
Access 100+ models through serverless endpoints – including Llama 3, RedPajama, Falcon and Stable Diffusion XL. Endpoints are OpenAI compatible.
Test models in Chat, Language, Image, and Code Playgrounds.
Access 8 leading embeddings models – including models that outperform OpenAI's ada-002 and Cohere's Embed-v3 in MTEB and LoCo Benchmarks.
LONG CONTEXT QUALITY
QUALITY
MY MODELS
All your private dedicated endpoints and fine-tune models
Dedicated Endpoints for any model
Choose any kind of model — open-source, fine-tuned, or even models you've trained.
Choose your hardware configuration. Select the number of instances to deploy and how many you'll auto-scale to.
Tune for fast latency versus high throughput — simply by adjusting the max batch size.
Integrate Arvae Inference Engine into your application
Integrate models into your production applications using the same easy-to-use inference API for either Serverless Endpoints or Dedicated Instances.
Leverage the Arvae embeddings endpoint to build your own RAG applications.
Show streaming responses to your end users — almost instantly.
Perfect for enterprises — performance, privacy, and scalability to meet your needs.
Performance
You get faster tokens per second, higher throughput and lower time to first token. And, all these efficiencies mean we can provide you compute at a lower cost.
Control
Privacy settings put you in control of what data is kept and none of your data will be used by Arvae AI to train new models, unless you explicitly opt in to share it.
Autonomy
When you fine-tune or train a model with Arvae AI the resulting model is your own private model. You own it.
Security
Arvae AI offers flexibility to deploy in a variety of secure clouds for enterprise customers.
The Arvae Inference Engine sets us apart.
We built the blazing fast inference engine that we wanted to use. Now, we're sharing it with you.
The Arvae Inference Engine deploys the latest inference techniques:
FlashAttention 3 and Flash-Decoding
The Arvae Inference Engine integrates and builds upon kernels from FlashAttention-3 along with proprietary kernels for other operators.
Advanced speculative decoding
Our engine implements state-of-the-art speculative decoding techniques that accelerate generation by predicting multiple tokens at once, significantly reducing latency for real-time applications.
This allows the engine to generate content up to 2-3x faster than traditional token-by-token generation, especially for common patterns and responses.
Quality-preserving quantization
Our quantization techniques reduce model size and memory requirements without compromising on output quality, enabling efficient deployment of large language models on standard hardware.
Arvae's proprietary quantization methods preserve the nuanced capabilities of the original models while dramatically reducing their computational footprint.
Continuous batching and request pipelining
Our engine dynamically batches incoming requests to maximize GPU utilization, resulting in higher throughput and lower costs per request, while our pipelining architecture ensures minimal waiting time between processing stages.