SETTLEMENT TELEMETRY

Inference Log

MID: guoKp9G2g9AfMGGm

Log MIDguoKp9G2g9AfMGGm
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
285 × 4.05 = 0.001154
0 × 0.135 = 0.000000
3810 × 12.15 = 0.0463
CNY 0.0474
Vendor Cost
285 × 3.6 = 0.001026
0 × 0.12 = 0.000000
3810 × 10.8 = 0.0411
CNY 0.0422
Latency61.64049612s
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):需要考虑的权衡、如何度量与验证、在生产环境中、可观测性、并给出可落地的建议、分点阐述其中的、数据一致性、以及未来发展趋势、请详细说明、以及未来发展趋势、算法复杂度、背后的设计取舍、under high concurrency、潜",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "在云计算架构与分布式系统中部署机器学习 token generation 服务,必须权衡内存管理、算法复杂度与 latency distribution。下面分点阐述其中的关键原理与影响:生产环境 under high concurrency 的潜在风险是 KV cache 膨胀导致 OOM、长尾延",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 3810,
  "completion_tokens_details": {
    "reasoning_tokens": 3512
  },
  "prompt_tokens": 285,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 4095
}
Fixes
Created At9/8/2026, 7:33:14 PM