Inference Endpoints: Real-Time Inference Tuned to Your Workload

Deployed on dedicated infrastructure, sized to your latency targets, and traffic; billed at predictable monthly spend.

Built for Production

Dedicated GPUs, custom kernels, hybrid pricing, and engine selection per workload. Everything you’d build yourself if you had the team to build it.

Full Control

Single-tenant endpoints with dedicated SLA.

Scalable

Reserved baseline plus on-demand scale-up.

Cost Efficient

Hybrid pricing against a committed spend pool.

Fast

Custom CUDA kernels, vLLM or SGLang engine selection.

Access Leading Open-Source and Open-Weight Models

Run any open-source model with a HuggingFace checkpoint or bring your own fine-tuned weights, custom containers, or Helm charts.

Deploy within seconds.
OpenAI-compatible endpoints
Hybrid pricing with scale-to-zero

Proven Results

Consistent, high-performance inference – more tokens per second, lower latency, and optimized throughput even under heavy workloads.

Gemma 4 | 27b

Output throughput: 224 tokens per second | Time to first token: 132 ms

Endpoint configuration:

Context length: 256k
GPU used: 1x H100
Parallel queries: concurrency of 10 requests
Quantization: fp8

Qwen3.6 | 30B-A3B-Instruct

Output throughput: 412 tokens per second | Time to first token: 96 ms

Endpoint configuration:

Context length: 256k
GPU used: 1X H100
Parallel queries: concurrency of 10 requests
Quantization: fp8

GLM-5.1

Output throughput: 184 tokens per second | Time to first token: 318 ms

Endpoint configuration:

Context length: 200k
GPU used: 4X H100
Parallel queries: concurrency of 10 requests at a time
Quantization: fp8

Built for Full Control and Customization

Get dedicated single-tenant inference endpoints running on vLLM, deployed on reserved monthly GPUs for guaranteed availability and security and ability to customize every aspect of your endpoint

Per-workload kernel and engine selection (vLLM, SGLang, custom CUDA)
Forward-deployed engineering for benchmarking, fine-tuning, and RLHF
Deploy in your VPC, on-prem, air-gapped edge, or multi-cloud
Workspace-based access management for AI/ML teams

Customize with the Power of Top NVIDIA and AMD GPUs

NVIDIA configurations from L4 through Blackwell B300, plus AMD Instinct for teams that want a non-NVIDIA path. As new silicon ships, endpoints move across generations without re-architecting – and one cluster handles LLM, speech, and vision workloads side by side.

Comprehensive GPU configuration options
Enterprise-grade reliability and uptime
Optimized for AI and inference workloads

Security and Privacy-First Design

Security and compliance are built into every layer of Velocis – from physical infrastructure to model deployment – and audited against ISO 27001:2022, SOC 2, CSA STAR Level 2, ISO 27017, and ISO 27018. Neysa is also a CSA Trusted Cloud Provider.

Cloud & Infrastructure Security

Strict compliance and security controls ensure your data remains protected. Includes RBAC, audit logs, policy enforcement, encryption, and zero-trust access.