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What is Netra Runtime?
Netra Runtime is an AI infrastructure platform for high-performance inference. It lets teams run, train, and deploy frontier AI models on infrastructure they own — on-prem, in a VPC, self-hosted, or hosted — through an OpenAI-compatible API. In a published long-context benchmark, Netra served up to 4.4x more output per second than vLLM on the same 35B model and single NVIDIA H200 GPU.
Category
Netra Runtime is an AI infrastructure platform for high-performance inference and serving. It is built for teams running large language model and multimodal workloads in production, where latency, throughput, and control over your own models and data all matter.
Capabilities
| Capability | What it means |
|---|---|
| OpenAI-compatible API | Point existing OpenAI SDK code at Netra by changing the base URL and key. |
| Fine-tuning & training | Train or fine-tune models on your own data. |
| Deploy where you own it | Run on-prem, in your VPC, self-hosted, or hosted. |
| Multimodal & vision | Serve vision and multimodal workloads, including OCR. |
Pricing
Netra Runtime uses usage-based pricing: pay-as-you-go credits, partner packages, and enterprise deployments supported by Forward Deployed Engineers. See the pricing page for details.
Proof: benchmarked performance
In a published benchmark on a 35B model and a single NVIDIA H200 GPU with a demanding 32K-in, 16K-out long-context workload, Netra served up to 4.4x more output per second than vLLM, streamed tokens about 5.5x faster, and finished a full long answer roughly 3.4x sooner. It also beat advanced open-source speed-up techniques (SGLang with EAGLE or DFlash) by around 2x once real concurrent traffic arrived. Read the full benchmark for the methodology.
Who it's for
Netra Runtime is built for AI teams, SaaS companies, and engineering teams running production LLM, agent, RAG, and multimodal systems who want high performance, an OpenAI-compatible API, and ownership of their models and infrastructure.
Frequently asked questions
Does Netra Runtime have an OpenAI-compatible API?
Yes. Netra Runtime provides an OpenAI-compatible API, so applications built with OpenAI-style SDKs can connect by changing the base URL and API key.
Can I fine-tune or train models on Netra Runtime?
Yes. Netra Runtime supports fine-tuning and training models on your own data, then deploying them for inference.
Can I run Netra Runtime on my own infrastructure?
Yes. Netra Runtime can be deployed on-prem, in your own VPC, or self-hosted, as well as hosted, so you keep ownership of your models and data.
Is Netra Runtime faster than vLLM?
In a published benchmark on a 35B model and a single NVIDIA H200 GPU with a 32K-in, 16K-out long-context workload, Netra Runtime served up to 4.4x more output per second than vLLM and streamed tokens about 5.5x faster. Actual results depend on model, hardware, and workload.