Skip to main content
RunInfra is an AI-powered platform that lets you describe the endpoint you need in plain English and handles everything else: model selection, GPU benchmarking, optimization, deployment, and scaling. Whether you’re building a low-latency chatbot, a batch summarization API, or a multi-model reasoning pipeline, you go from idea to live endpoint without writing infrastructure code. No YAML. No DevOps. No GPU configuration. Just chat.

​
What you can build

RunInfra can build large language model, speech-to-text, text-to-speech, embedding, vision-language, and image-generation pipelines when the selected model and runtime support the route. Six pre-built use cases ship as starting points you can fork in chat.

Voice agents

Streaming STT, LLM, and TTS fused on one GPU at sub-600ms turn-taking.

AI assistants

Llama, Hermes, Qwen with tool use, streaming, and structured output.

Embeddings + rerank

BGE encoders + cross-encoder reranker fused on one GPU in one round-trip.

RAG search

Hybrid retrieval, grounded generation, citation spans you can audit.

Document AI

Qwen2.5-VL and Llama 3.2 Vision parsing PDFs and forms to JSON.

Transcription

Open Whisper with diarization and PII redaction.

​
Example prompts

Copy any of these into the dashboard chat to see how it works. 
Deploy Llama 3.1 8B as a low-latency customer support chatbot.
Optimize for latency, keep P99 under 200ms.

Build a multi-model pipeline: Phi-3 Mini for simple queries,
Llama 70B for complex reasoning. Budget is $300/month.

Optimize Qwen 2.5 14B for throughput and deploy as a batch
summarization API. Max $0.003 per request.

I need a code generation endpoint using DeepSeek V3.
Keep cost under $0.005 per request.
The agent handles model selection, GPU benchmarking, optimized variant search, kernel optimization, deployment, and autoscaling.

​
How it works

A four-stage workflow from description to live endpoint.

Describe

Tell RunInfra what you need in plain English. The agent asks clarifying questions when needed, then builds your pipeline automatically.

Optimize

Real GPU profiling across L4 to B200, Hugging Face variant search (AWQ, GPTQ, FP8), and Forge kernel tuning. Results stream in real time.

Deploy

One click ships an OpenAI-compatible endpoint. Flex (scale-to-zero) or Active (always-on). Cold starts under 2 seconds.

Integrate

OpenAI Python and JavaScript SDKs, curl, and documented framework integrations use your RunInfra base URL and deployed model ID.

​
Why RunInfra

Closed-source APIs charge per token with no control over latency, throughput, or cost. With RunInfra you own the model and the infrastructure. RunInfra optimizes GPU kernels so your open-source models run as fast as, or faster than, proprietary APIs at a fraction of the cost.

​
Get started

Quickstart

Your first pipeline in 5 minutes.

Use cases

Pre-built workflows you can fork in chat.

Which model?

Decision table by use case and priority.

Deployments

Flex vs Active, deployment targets, scaling.