GPT-Image-2.5 Flare
GPT-Image-2.5 Flare is a hosted image-generation model available through the OpenAI API. It accepts text prompts and image inputs and produces image outputs. Developers can call it through the Images API to generate images or edit supplied images, or use it as an image-generation tool within Responses API workflows that support conversations and multiple steps. Requests can set image quality to low, medium, high, xhigh, max, or auto, and configure output size, format, and compression. OpenAI positions Flare for fast, everyday image generation, while its GPT-Image-2.5 Sunburst model is intended for workflows prioritizing precise editing. The model is designed for developers and organizations adding image creation or editing to their own applications. Access requires API credentials, and usage is billed by tokens, with rates depending on text or image input, image output, and standard or batch processing.
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Velokey
Velokey is a unified AI model API platform that gives developers access to leading text, image, and video models through one interface. The platform supports LLM APIs, image generation APIs, and video generation APIs, allowing teams to switch models without rebuilding integrations. Developers can use an OpenAI-compatible SDK by changing the base URL and API key, then selecting the model they want to call. Velokey includes models from families such as GPT, Claude, Gemini, DeepSeek, Grok, Kimi, Qwen, GLM, Seedance, Kling, Veo, Wan, Nano Banana, GPT Image, and more. The platform also provides smart model routing, automatic failover, usage tracking, latency visibility, spend monitoring, and transparent pricing across tokens, images, and video seconds. Built for developers and AI teams, Velokey helps simplify model access, reduce integration overhead, and manage multiple AI providers from one API and one bill.
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Oridica
Ordica is an AI infrastructure layer designed to reduce the cost of using large language models by compressing prompts before they are sent to providers like GPT-4o, Claude, Gemini, or Grok. It operates as a lightweight proxy that sits directly in the request path, requiring no new dependencies. Users simply point their existing SDK to Ordica’s endpoint and continue using their current API keys unchanged. It processes prompts entirely in memory, compressing them in transit and forwarding them to the selected provider without storing, logging, or retaining any message content, ensuring that data privacy is preserved at every step. Ordica dynamically decides whether to compress a request based on confidence thresholds; if compression is expected to preserve output quality, it reduces token usage; if not, the request passes through unchanged, guaranteeing no degradation in responses. This approach allows developers to achieve measurable cost savings across different workloads.
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condense.chat
condense.chat is an LLM input compression API and drop-in proxy that shrinks prompts, retrieved documents, tool outputs, and repeated agent context before they hit upstream models. Less context, same Claude Code; its harness intercepts an agent’s growing session history and passes it through compression models before it reaches the main model, helping long-running coding agents start each next turn with fewer tokens. Condense sits between an app and the upstream LLM provider, tracks the conversation as a content-addressed chain, and transparently compresses repeated context on the way upstream. Developers can point their SDK at the Condense provider route, add a Condense key, keep their existing provider key, and change nothing else. It supports Anthropic and OpenAI-compatible routes, plus pass-through behavior for other provider paths such as model lists and embeddings.
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