RunInfra

Benchmark, tune, and deploy ML models to production in minutes

Unclaimed

Added Jul 2026

runinfra.ai

Developer AppsFreedeveloper-apps

Visit Runinfra

Share: X in LinkedIn

Add your screenshot here

Image or video shown in this spot

Get Verified · $10 lifetime

Follow Runinfra

What is Runinfra?

RunInfra is an AI model optimization platform that automatically benchmarks inference serving engines, tunes configurations, and generates production-ready deployment stacks. Users describe their inference workload in plain English, and the system compares serving engines (vLLM, SGLang, TensorRT-LLM, etc.), measures performance metrics like latency and throughput, and provides either a managed deployment option or an exportable stack for self-hosting. It's built for ML teams and engineers deploying large language models and embeddings to production.

Explore Runinfra

Need help implementing RunInfra?

Find verified specialists who work with RunInfra

Browse specialists

Key Features of Runinfra

AI-driven serving engine comparison
Automatic GPU sizing and optimization
P95 latency benchmarking
Throughput measurement per GPU
VRAM fit validation
Cost tracking per run
GPU kernel tuning
Deployment kit generation
Plain English workload description
Quantization support (AWQ int4)
FlashAttention v2 integration
Continuous batching
Paged KV cache optimization
CUDA graph capture
Speculative decoding
Prefix caching
Tensor-parallel sizing
Automatic warmup and autotuning
Serving configuration tuning

Who Should Use Runinfra?

Optimize large language models for low-latency inference

Deploy speech-to-text models with performance guarantees

Scale embedding models for retrieval workflows

Compare inference serving engines for model compatibility

Reduce cost while maintaining latency SLAs

Tune GPU utilization for production deployments

Runinfra: Pros & Cons

✓Pros

Transparent benchmarking with detailed result inspection
No hidden configuration or black-box optimization
Supports multiple inference engines and models
Generates runnable deployment kits
Automatic tuning removes manual configuration
Cost tracking per optimization run
Scalable from single GPU to multi-GPU setups

Frequently Asked Questions about Runinfra

What is RunInfra?

RunInfra is a platform that optimizes AI model inference by benchmarking serving engines, tuning configurations, and generating production-ready deployment stacks. You describe your workload in plain English, and the system compares engines, measures performance, and provides a deployment kit you can run or export.

Which inference engines does RunInfra support?

RunInfra compares multiple serving engines including vLLM, SGLang, TensorRT-LLM, and others compatible with your model.

What models can I optimize?

RunInfra supports large language models (like Llama, Qwen) and embeddings models (like BGE-M3), plus speech models like Whisper.

Can I deploy RunInfra's optimization or self-host?

You can deploy directly on managed infrastructure (like NVIDIA A100) with per-token pricing, or export the full stack for self-hosting.