{
  "experiment": "ai-visibility-baseline",
  "description": "Monthly public experiment: do LLMs recommend Argosvix when asked (from their own training data, no web search) for LLM observability tools, and do they recognize the name at all?",
  "page": "https://argosvix.com/en/ai-visibility",
  "questions": {
    "q1": "I'm building an AI agent that calls multiple LLM APIs in production. What observability / monitoring tools would you recommend for tracking cost, latency, errors and quality of the LLM calls? List up to 8 tools with one line each.",
    "q2": "Do you know a developer tool called \"Argosvix\"? If yes, describe what it does in 2-3 sentences. If you have never heard of it, just say so honestly."
  },
  "conditions": {
    "web_search": false,
    "system_prompt": null,
    "temperature": 0.3,
    "notes": "Kimi K3 only accepts temperature 1 (API constraint). q1_top_tools is the recommendation list the model returned for Q1, in the model's own order (null where the full answer text was not archived; the mention check was still negative)."
  },
  "measurements": [
    {
      "date": "2026-08-10",
      "models": [
        {
          "model": "grok-4.5",
          "vendor": "xAI",
          "measured": true,
          "q1_mentioned": false,
          "q2_recognized": false,
          "q1_top_tools": [
            "LangSmith",
            "Langfuse",
            "Helicone",
            "Portkey",
            "Arize Phoenix",
            "Datadog LLM Observability",
            "Braintrust",
            "Galileo"
          ]
        },
        {
          "model": "deepseek-chat",
          "vendor": "DeepSeek",
          "measured": true,
          "q1_mentioned": false,
          "q2_recognized": false,
          "q1_top_tools": [
            "Langfuse",
            "Helicone",
            "LangSmith",
            "Arize Phoenix",
            "Wandb Weave",
            "Portkey",
            "Traceloop"
          ]
        },
        {
          "model": "kimi-k3",
          "vendor": "Moonshot",
          "measured": true,
          "q1_mentioned": null,
          "q2_recognized": false,
          "q1_top_tools": null,
          "q1_note": "empty response; recommendation list could not be collected"
        },
        {
          "model": "mistral-large-latest",
          "vendor": "Mistral",
          "measured": true,
          "q1_mentioned": false,
          "q2_recognized": false,
          "q1_top_tools": [
            "LangSmith",
            "Arize AI",
            "Weights & Biases",
            "Helicone",
            "Prometheus + Grafana",
            "Datadog",
            "OpenTelemetry",
            "Lunary"
          ]
        },
        {
          "model": "qwen3.8-max",
          "vendor": "Alibaba",
          "measured": true,
          "q1_mentioned": false,
          "q2_recognized": false,
          "q1_top_tools": [
            "Langfuse",
            "LangSmith",
            "Helicone",
            "Arize Phoenix",
            "Datadog LLM Observability",
            "Braintrust",
            "OpenLLMetry / Traceloop",
            "Weights & Biases Weave"
          ]
        },
        {
          "model": "gpt",
          "vendor": "OpenAI",
          "measured": false
        },
        {
          "model": "claude",
          "vendor": "Anthropic",
          "measured": false
        },
        {
          "model": "gemini",
          "vendor": "Google",
          "measured": false
        }
      ],
      "summary": {
        "q1_mentions": "0/5",
        "q2_recognitions": "0/5"
      }
    }
  ]
}