SETTLEMENT TELEMETRY

Inference Log

MID: guw1Rwt6OA2Ad9hi

Log MIDguw1Rwt6OA2Ad9hi
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
1601 × 12.15 = 0.0195
CNY 0.0203
Vendor Cost
218 × 3.6 = 0.000785
0 × 0.12 = 0.000000
1601 × 10.8 = 0.0173
CNY 0.0181
Latency27.79249534s
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):token generation、如何度量与验证、需要考虑的权衡、需要考虑的权衡、streaming response、背后的设计取舍、cache strategy、可观测性、请举例说明、潜在的风险点、如何度量与验证、从技术角度",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "在 AI 推理云计算架构中,token generation 是核心路径,常以 streaming response 降低首字延迟。设计取舍需在吞吐、延迟与成本间权衡:cache strategy 可复用前缀 KV,但引入内存管理与并发控制复杂度,并可能引发缓存击穿。可观测性需度量 TTFT、tok",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 1601,
  "completion_tokens_details": {
    "reasoning_tokens": 1390
  },
  "prompt_tokens": 218,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 1819
}
Fixes
Created At9/9/2026, 6:42:34 PM