Hey Product Hunt 👋
I’m porter, one of the makers of Velokey.
Today, we’re launching Velokey—one OpenAI-compatible API for accessing leading AI models without managing a separate integration, API key, and billing account for every provider.
Our live catalog currently includes 63 models from 14 providers:
• 41 chat and reasoning models• 9 image-generation models• 13 video-generation models
That includes models from OpenAI, Anthropic, Google, DeepSeek, xAI, ByteDance, Alibaba, Kuaishou, and others.
We built Velokey around a simple belief: the best model for your product will keep changing, but your integration shouldn’t have to.
With Velokey, you can:
• Keep your existing OpenAI SDK and change only the Base URL and API key• Switch between models by changing the model ID• Compare pricing before making a call• Track requests, token usage, latency, errors, and spending in one console• Use automatic failover when multiple healthy routes are available• Pay as you go, with no subscription or minimum spend
Pricing is also a big part of what we’re trying to improve. Of the 63 models currently available, 58 are offered below their listed official prices, with savings ranging from 20% to 80% depending on the model.
We also don’t retain prompt or model-output content.
We’re still early, and we’d genuinely love your feedback:
Which models or integrations should we prioritize next? And what would you need to see before trusting a unified AI API in production?
Thanks for checking out Velokey ❤️
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It would be really helpful to see latency benchmarks alongside the pricing comparison, since faster response times matter as much as cost for a lot of use cases. Adding p50 and p95 latency stats per model would make it way easier to pick the right one for real-time apps.
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One OpenAI-compatible endpoint across 100+ models is a crowded but real need — how are you sourcing the 20–80% savings, reselling upstream capacity or arbitraging provider price differences? Also curious whether you expose an Anthropic-compatible /v1/messages endpoint, since a lot of the Claude Code crowd needs that shape specifically.
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It would be really helpful to see latency benchmarks alongside the pricing comparison, since faster response times matter as much as cost for a lot of use cases. Adding p50 and p95 latency stats per model would make it way easier to pick the right one for real-time apps.
One OpenAI-compatible endpoint across 100+ models is a crowded but real need — how are you sourcing the 20–80% savings, reselling upstream capacity or arbitraging provider price differences? Also curious whether you expose an Anthropic-compatible /v1/messages endpoint, since a lot of the Claude Code crowd needs that shape specifically.