SETTLEMENT TELEMETRY

Inference Log

MID: guw12QkIBsyNRMbm

Log MIDguw12QkIBsyNRMbm
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
218 × 4.05 = 0.000883
0 × 0.135 = 0.000000
1971 × 12.15 = 0.0239
CNY 0.0248
Vendor Cost
218 × 3.6 = 0.000785
0 × 0.12 = 0.000000
1971 × 10.8 = 0.0213
CNY 0.0221
Latency39.83359056s
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 200 tokens 的输入):load balancing、机器学习、碳中和、云计算架构、latency distribution、人工智能、潜在的风险点、请举例说明、结合实际案例、云计算架构、请详细说明、人工智能、分布式系统、机器学习、从技术角度分析、st",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "在云计算架构与分布式系统中,负载均衡策略会直接影响 latency distribution。机器学习/人工智能推理常用 streaming response 进行 token generation,其算法复杂度与调度设计取舍可能放大尾部延迟,这是潜在风险点。结合实际案例,某云厂商在 LLM 推理集",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 1971,
  "completion_tokens_details": {
    "reasoning_tokens": 1780
  },
  "prompt_tokens": 218,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 2189
}
Fixes
Created At9/9/2026, 6:41:22 PM