SETTLEMENT TELEMETRY

Inference Log

MID: guoIxzK0vGpXQ5vd

Log MIDguoIxzK0vGpXQ5vd
Typechat_completion
Aliasdeepseek-v4-pro-g3 / gucs9pv3TRoBtepN
Hostinforaxi-server:3300:v1.1.4013-14-gbfebabe6d
Mode / Protoreq-v1-chatcmplopenai-chatcmpl
Vendor/LLMvolcengine-bizplan-dtx/deepseek-v4-pro-ga-260813
Statussuccess
User Pricing
288 × 4.05 = 0.001166
0 × 0.135 = 0.000000
2286 × 12.15 = 0.0278
CNY 0.0289
Vendor Cost
288 × 3.6 = 0.001037
0 × 0.12 = 0.000000
2286 × 10.8 = 0.0247
CNY 0.0257
Latency39.37277260s
Summary
{
  "system_prefix": null,
  "history_count": 1,
  "user_summary": {
    "text": "请围绕下面的关键词写一段连贯的分析(约 300 tokens 的输入):结合实际案例、人工智能、潜在的风险点、load balancing、token generation、潜在的风险点、分布式系统、以及未来发展趋势、性能优化、算法复杂度、结合实际案例、潜在的风险点、请详细说明、性能优化、cache",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "在生产环境中,某人工智能在线助手采用大模型 streaming response,每次请求都触发 token generation。under high concurrency 下,分布式系统通过 load balancing 将请求分发到多推理节点,但实际案例中 latency distribut",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 2286,
  "completion_tokens_details": {
    "reasoning_tokens": 1992
  },
  "prompt_tokens": 288,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 2574
}
Fixes
Created At9/8/2026, 7:27:49 PM