Overview
Velokey is a unified AI API gateway that consolidates access to over 100 text, image, and video generation models from providers including OpenAI, Anthropic, Google, ByteDance, Alibaba, and xAI through a single OpenAI-compatible endpoint. Developers can test, compare, and switch between GPT, Claude, Gemini, Seedance, Kling, Veo, and dozens of other models by changing one parameter—without rewriting client code or managing multiple vendor accounts.
How Velokey Works
Velokey sits between your application and AI model providers. If you already use an OpenAI SDK, migration requires two changes: update your base URL to api.velokey.ai/v1 and replace your API key with a Velokey key. From there, you can call any supported model by specifying its identifier in the request. The platform handles routing, authentication, and response formatting across all providers.
The gateway supports three modalities. For text generation, you can access GPT-5.5, Claude Opus 4.8, Gemini 3 Pro, DeepSeek v4, Grok 4.3, and language models from Kimi, MiniMax, Qwen, GLM, and ERNIE. For image generation, models include GPT Image 2, Nano Banana Pro, Qwen Image 2.0, Doubao Seedream 5.0, Kling v3 Image, and Grok Imagine. For video, Velokey provides access to Seedance 2.0, Kling v3 Video, Veo 3.1, Wan 2.7, Vidu Q3, PixVerse V6, and HappyHorse 1.1.
Smart Routing and Failover
Velokey's routing layer checks latency and availability across provider endpoints in real time. When multiple routes exist for a model, requests go to the faster, more stable option. If an upstream provider returns an error or times out, the system moves the request to a healthy fallback route automatically. This reduces the need for manual retry logic and monitoring of individual provider status pages.
The console shows request success rate, latency distribution, and per-model spend over the last 30 days. Each API call is metered separately, and the dashboard breaks down token usage, image count, or video seconds depending on the model type.
Model Comparison and Pricing
Velokey publishes benchmark scores, context limits, and pricing for each model family. For language models, comparison tables show GPQA (graduate-level reasoning), SWE-bench (code-fixing ability), and LMArena (human preference) scores alongside input and output token costs. For example, GPT-5.5 is listed at $4–5 per million input tokens and $24–30 per million output tokens, while Claude Sonnet 4.6 is priced at $3 per million input tokens.
Image models are billed per image generated, and video models are billed per second of output. Pricing is visible before you make a call, and you only pay for actual usage—no monthly minimums or seat-based plans.
Who Uses Velokey
Velokey targets backend developers and AI product teams who need model flexibility without vendor lock-in. Startups use it to prototype with multiple models before committing to one provider. Teams building multi-modal applications—combining text analysis, image generation, and video synthesis in a single pipeline—consolidate API management under one account and billing flow.
Developers migrating from OpenAI to Claude or Gemini can test the swap in production-like conditions by changing one line of configuration. Teams comparing model performance across providers use the benchmark tables and usage logs to evaluate quality and cost before scaling.
Access and Privacy
Velokey operates on a pay-as-you-go model with no upfront cost. You create an account, generate an API key from the console, and start calling models. The platform does not store prompt or output content and does not use customer API data for training. Metadata is retained for billing, security monitoring, and support, but request payloads are not logged.
The service is available in eight languages, including English, Chinese, Spanish, Japanese, Korean, German, French, and Russian. API documentation covers authentication, request formatting, rate limits, and error codes for each model family.
