Oxlo.ai vs Router by Ramp: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Oxlo.ai and Router by Ramp — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Oxlo.ai
Oxlo
Privacy-first inference platform to run Kimi K2.6, DeepSeek, and 45+ open-source models on a flat-priced, OpenAI-compatible API.
Key features
- OpenAI-compatible API: Drop-in API that serves 45+ open-source models so existing OpenAI client code works without rewrites.
- Flat monthly pricing: A fixed subscription instead of per-token billing, keeping inference bills predictable at any scale.
- Privacy-first inference: Zero data retention and no training on your data, so prompts and outputs stay private.
- Unlimited agentic tool calls: Run agent workflows with tool calling without metered per-call charges.
- Secure failover: Automatic routing and failover across models to keep agents reliable under load.
- Cost calculator: Compare your current inference spend against Oxlo and competing providers before committing.
- Broad model catalog: Access frontier open models like Kimi K2.6, DeepSeek V4 Flash, GLM-5, Llama, and Qwen plus Whisper, TTS, and image models.
Best for
- Building chatbots and AI assistants for support and internal tools on open models.
- Powering document Q&A and retrieval-augmented generation over PDFs and knowledge bases.
- Generating, rewriting, and summarizing text inside apps and internal systems.
- Running image understanding tasks such as classification and object detection.
- Cutting and stabilizing inference costs for AI teams with high, variable token usage.
Router by Ramp
Ramp
Ramp's LLM gateway routes each request to the cheapest model meeting your quality bar, cutting inference costs ~40% behind one endpoint and one bill.
Key features
- Cost-Aware Automatic Routing: Every request is matched to the lowest-cost model that still meets your performance requirements, reported to cut inference spend by about 40% on average.
- One Key for Every Model: Closed and open-source models from vetted providers sit behind a single endpoint, key and invoice.
- Rolling Strategy Updates: New cost-saving routing strategies and newly benchmarked default models roll in automatically without changing your integration.
- Score Versus Spend Reporting: Built-in benchmarking shows metric distributions and model summaries so you can see quality and cost side by side.
- Flex Tier Routing Share: A tunable split between default and flexible routing lets you dial how aggressively requests are shifted to cheaper models.
- US-Hosted Providers with ZDR: All vetted providers are US-hosted, with zero-data-retention options for sensitive workloads.
- Switchyard Integration: Works with Switchyard for model and provider routing, surfaced directly in the CLI's cost display.
- One-Command CLI Setup: Install and configure with a single curl command from agents.ramp.com, with an agent-friendly copy-paste flow.
Best for
- Trimming Production Inference Spend: Route high-volume, low-difficulty requests to cheaper models while keeping frontier models for the hard ones — Delphi reports a 92% model cost reduction across billions of tokens.
- Multi-Provider Consolidation: Replace separate OpenAI, Anthropic and open-model integrations with one endpoint and one bill.
- Model Benchmarking Before Migration: Test candidate models against your real workloads and compare score against spend before switching defaults.
- Finance and Engineering Alignment: Give CFOs a single, attributable AI spend line while engineers keep the best model for each workload.
- Compliance-Constrained Deployments: Keep inference on US-hosted providers with zero-data-retention options for regulated data.
- Agent Cost Control: Cap the runaway token spend of long-running agent loops by routing their routine steps to cheaper models automatically.