HiveOps - Distributed AI inference at any scale

Hey Product Hunt! 👋 I’m Adeniyi, co-founder of HiveOps. We built HiveOps because we were tired of the "black box" pricing of AI APIs. When you use legacy cloud providers, you aren’t just paying for compute; you are paying for their massive corporate overhead and arbitrary markups. We decided to change the math. HiveOps is a drop-in OpenAI-compatible API that is up to 80% cheaper than GPT-4o, powered by the best open-source models (Llama 3, Qwen, Gemma 3, and more). How are we doing this without burning VC cash on cloud GPUs? We completely re-architected the infrastructure layer: - Bare-Metal Efficiency: We run highly quantized models on optimized, dedicated hardware. - Physics-Based Pricing: We don't guess at pricing. We built a billing engine that prices tokens based on the actual physics of LLM inference. Here is our transparent pricing formula: - Inputs (Compute-bound): Priced strictly on a model's parameters. - Outputs (Memory-bound): Priced on Parameters and Quantization bits. (We pass the VRAM bandwidth savings of 4-bit and 8-bit models directly to your wallet). You can swap out your api.openai.com base URL for ours in about 5 seconds. 🎁 Launch Promo for the PH Community: To celebrate our launch, we are running a 100% Deposit Match (up to $50) on your first top-up. There are no expiring credits or weird Stripe coupon hacks, just pure added purchasing power tracked transparently in your developer ledger. We’d love for you to try it out, break things, and let us know which open-source models you want us to add to the nodes next. My co-founder and I will be in the comments all day answering questions about our infrastructure, our pricing formula, or anything else!