RunInfra

RunInfra makes model deployment as simple as chatting. You describe the AI you need—latency, cost targets, model type—and the platform automatically selects compatible open-source models, benchmarks GPUs, optimizes kernels and quantization, and deploys a serverless API. It supports not just LLMs, but also voice, transcription, TTS, and embeddings.

The key advantage is removing ops complexity: no kernel tweaking, no GPU selection, no manual quantization. Pricing is pay-per-million-tokens with scale-to-zero, and they claim SOC 2 Type II compliance. This lets lean teams own their AI stack without managing infrastructure.

However, the product is still in public beta, so stability at scale, the full list of supported models, and extreme-load performance remain unverified. If you need a niche open-source model or a highly customized inference graph, compatibility is uncertain. And while token-based billing is clear, the exact price points are not publicly documented, making it hard to forecast large-scale costs.

RunInfra fits startups and agile teams that want to rapidly productionize open-source models without building GPU clusters.