Oxlo.ai

Oxlo.ai provides hosted inference for a catalog of open-source models via a REST API that mirrors the OpenAI request format. Developers point existing OpenAI SDK integrations at Oxlo’s endpoint, swap the base URL and API key, and gain access to models including DeepSeek R1 671B, Kimi K2.6, Llama 3.3 70B, Whisper v3, Kokoro TTS, BGE-Large, SDXL, and YOLOv11 — covering text, image, audio, embeddings, and object detection in a single billing account. The vendor also lists OxCompute as a forthcoming product, though no details are available on the page.

The differentiating claim is the combination of flat-rate pricing and a stated zero-data-retention policy. The vendor states that requests are not used for model training and are not stored after processing — a meaningful distinction if you’re handling legal documents, medical records, or proprietary enterprise data. The paid plan is a single flat monthly fee rather than per-token metering, which means a spike in usage does not produce a spike in your bill. The vendor’s own cost calculator confirms that per-token alternatives are cheaper at low volumes, so this pricing model is strictly advantageous at scale.

Oxlo.ai fits teams that have already validated their use case and are moving to production at volume — chatbots, document Q&A pipelines, batch transcription, or embedding generation where monthly token counts are high and cost predictability matters. It does not fit teams that need to self-host or run models inside their own VPC, since no self-hosted deployment option is offered. The service is also not an agent framework — there is no canvas, no workflow builder, and no visual tooling; it is an inference endpoint that agents you build elsewhere call. Teams that need workflow orchestration build that layer themselves and treat Oxlo.ai purely as the model backend.