AI API
Oxlo.ai
Oxlo.ai is a privacy-first AI inference API offering request-based pricing for over 45 open-source models.
Oxlo.ai
What is Oxlo.ai?
Oxlo.ai is an AI inference API that provides request-based pricing for a wide range of open-source models, including Kimi K2.6, with a focus on privacy and no data retention.
Oxlo.ai vs Similar AI Tools
| Pricing Model | Free, Free Trial, Paid | Free, Freemium | Free, Free Trial, Custom Pricing | Free, Freemium |
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How to use Oxlo.ai?
- 1Sign up at oxlo.ai and generate an API key.
- 2Install the OpenAI Python or Node.js SDK.
- 3Change the base_url parameter to https://api.oxlo.ai/v1.
- 4Replace your API key with the Oxlo.ai key.
- 5Start making API calls with standard OpenAI-compatible code.
Oxlo.ai Key Features
- Request-based pricing (flat fee per API call, independent of token count)
- Over 45 open-source and frontier models including Kimi K2.6, DeepSeek, Llama, and Qwen
- Privacy-first: zero data retention and no training on user prompts
- Unlimited agentic tool calls with secure failover
- OpenAI-compatible API for seamless migration
- Free tier with 60 requests/day and no credit card required
Oxlo.ai Use Cases
- Chatbots & AI Assistants
- Document Q&A and RAG
- Text Generation & Summarization
- Image Understanding and Classification
- Speech-to-Text and Text-to-Speech
- Batch AI Processing
Oxlo.ai Pricing & Free Credits
Oxlo.ai currently operates on a Free, Free Trial, Paid model.
This tool is completely free to use
Oxlo.ai Pros & Cons
Pros
- Predictable flat-rate pricing eliminates surprise bills from long-context requests
- Privacy-first: no data retention or training on user inputs
- Wide selection of open-source and frontier models
- Drop-in replacement for OpenAI SDK with only a base_url change
Cons
- Free tier limited to 60 requests per day
- Request-based pricing may be less economical for very short, low-token requests
- Smaller overall model catalog compared to some token-based providers
What is Oxlo.ai best for?
- Teams running large reasoning models in production
- Developers seeking predictable AI inference costs
- Privacy-conscious organizations
- Long-context workloads like RAG and document analysis