A developer built a lightweight Python harness to compare production-grade open large language models from Oxlo.ai. The harness sends identical prompts to four models—Llama 3.3 70B, Qwen 3 32B, Kimi K…
Oxlo.ai's request-based pricing enables developers to build a conversational language tutor that corrects mistakes in real time and adapts to learner proficiency. Using the llama-3.3-70b model via the…
Oxlo.ai offers request-based pricing for LLM-driven named entity recognition, making it economically viable for long documents. The platform supports structured output via JSON mode and function calli…
A developer shipped a small research agent that addresses three common LLM limitations: stale training data, hallucinated facts, and arithmetic errors. The agent uses tool calling to look up facts and…
A developer built a Python CLI tool that uses Oxlo.ai's LLM to evaluate whether a business task is suitable for automation with a large language model. The tool sends a task description to the llama-3…
Oxlo.ai offers flat per-request pricing for LLM APIs, decoupling cost from context size and enabling long-context applications without token-based billing. The company provides techniques such as prom…
Oxlo.ai is building an autonomous research agent that converts vague questions into structured plans, gathers evidence across multiple LLM calls, and synthesizes markdown reports. The agent uses small…
Oxlo.ai has introduced a request-based pricing model and an OpenAI-compatible API supporting over 45 models across seven categories, addressing the cost unpredictability of token-based billing for lon…
Oxlo.ai offers request-based pricing for AI inference, charging a flat fee per API call regardless of prompt length, contrasting with token-based models used by providers like Together AI and Firework…
A developer compared LLM inference APIs on cost, performance, and integration, noting that most providers use token-based pricing which can cause unpredictable costs for long-context or agentic worklo…