SETTLEMENT TELEMETRY

Inference Log

MID: guoL0AbwQ4aSpAmA

Log MIDguoL0AbwQ4aSpAmA
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
289 × 4.05 = 0.001170
0 × 0.135 = 0.000000
1400 × 12.15 = 0.0170
CNY 0.0182
Vendor Cost
289 × 3.6 = 0.001040
0 × 0.12 = 0.000000
1400 × 10.8 = 0.0151
CNY 0.0162
Latency26.63617519s
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):load balancing、潜在的风险点、cache strategy、关键原理与影响、streaming response、请详细说明、需要考虑的权衡、如何度量与验证、人工智能、潜在的风险点、cache strategy、背",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "从技术角度分析,在生产环境的云计算架构中,人工智能推理服务采用 streaming response 的关键原理是将 token generation 过程增量下发,以降低首字延迟并改善交互体验,但这会引入潜在的风险点:长连接会占用负载均衡后的后端资源,若 load balancing 未结合请求长",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 1400,
  "completion_tokens_details": {
    "reasoning_tokens": 1109
  },
  "prompt_tokens": 289,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 1689
}
Fixes
Created At9/8/2026, 7:33:45 PM