Cloud
Private Inference for Sensitive Workloads
Deploy inference in minutes with hardware-backed security that protect data, IP, and users.
NEAR AI Enables You To
Protect sensitive workloads with hardware-backed trust. Exceed existing privacy standards with a trustless system.
Know exactly how and where your data is processed. Gain cryptographic proof that every inference stays private and unaltered.
Stay agile as your needs evolve. Switch models, scale workloads, and avoid vendor lock-in without changing a line of code.
Go live fast. Cut deployment time and let teams focus on building products, not managing infrastructure.
Process sensitive data without extra tools or layers. Built-in isolation reduces complexity and operational overhead.
Solutions
Run sensitive workloads in total privacy.
Easily work with personal, proprietary, or regulated data in a hardware-secured environment that exceeds global compliance standards. Encryption and real-time verification ensure that no one can access your data.
Deploy private inference fast.
Integrate through one API and move from prototype to production in minutes. Each request runs in hardware-isolated environments that keep user data and IP protected.
Sovereign AI, delivered anywhere
Run AI workloads inside environments that keep sensitive and classified data under your control, even outside your borders. TEEs and real-time verification deliver sovereign control and compliance at global scale.
Models + Pricing
GLM-4.6 FP8 is Zhipu AI’s cutting-edge large language model with 358 billion parameters, quantized in FP8 for efficient inference.
200K context|$0.75/M input tokens|$2/M output tokens
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases.
131K context|$0.2/M input tokens|$0.6/M output tokens
DeepSeek V3.1 is a hybrid model that supports both thinking mode and non-thinking mode. Compared to the previous version, this upgrade brings improvements in multiple aspects.
128K context|$1/M input tokens|$2.5/M output tokens
Qwen3-30B-A3B-Instruct-2507 is a mixture-of-experts (MoE) causal language model featuring 30.5 billion total parameters and 3.3 billion activated parameters per inference.
262K context|$0.15/M input tokens|$0.45/M output tokens
Contact Us to Learn More About Pricing for Custom Models and Enterprise Deployment
Fast. Private. Always Available.
95% of requests complete in <100ms
1,000+ requests/second per node with auto-scaling. 200K token context windows with <5% latency impact Scale-out in <3 minutes for small models, <5 minutes for large models.
<30 second attestation verification 100% TLS 1.3 encryption, AES-256 at rest.HSM-backed key rotation every 90 days
99.5% monthly uptime for confidential enclaves. Real-time monitoring with immutable audit logs
