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    Introducing AutoEvals: Find the right model for your task

    OpenAIMultimodal Model

    GPT-6 Astra

    OpenAI's GPT-6 flagship for the hardest agentic coding and knowledge-work tasks: a 922K-token context with image input, tool calling, structured outputs, and reasoning effort from none up to xhigh. Built for deep multi-step work where quality dominates cost.

    import OpenAI from "openai";
    
    const openai = new OpenAI({
      baseURL: "https://api.inference.net/v1",
      apiKey: "<YOUR_API_KEY>",
    });
    
    const completion = await openai.chat.completions.create({
      model: "gpt-6-astra",
      messages: [
        {
          role: "user",
          content: "What is the meaning of life?"
        }
      ],
      stream: true,
    });
    
    for await (const chunk of completion) {
      process.stdout.write(chunk.choices[0]?.delta.content as string);
    }
    Prompt caching
    1. Keep the prompt prefix byte-identical across calls: same text, same order.
    2. Pass a stable prompt_cache_key string. It is a routing-affinity hint; it does not create or identify cached content.
    3. Check usage.prompt_tokens_details.cached_tokens in the response to confirm cache reads.
    {
      "model": "gpt-4o",
      "prompt_cache_key": "v1-stable-prefix",
      "messages": [{ "role": "user", "content": "..." }]
    }

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    Serverless, OpenAI-compatible, and billed per token. No commitments.