SETTLEMENT TELEMETRY

Inference Log

MID: guudSMg0oKAIGgRk

Log MIDguudSMg0oKAIGgRk
Typechat_completion
Aliasdeepseek-v4-flash-g3 / gucs9pn4RAHUO73l
Hostinforaxi-server:3300:v1.1.4013-14-gbfebabe6d
Mode / Protoreq-v1-chatcmplopenai-chatcmpl
Vendor/LLMvolcengine-bizplan-dtx/deepseek-v4-flash-ga-260731
Statussuccess
User Pricing
214 × 1.35 = 0.000289
0 × 0.045 = 0.000000
776 × 4.05 = 0.003143
CNY 0.003432
Vendor Cost
214 × 1.2 = 0.000257
0 × 0.04 = 0.000000
776 × 3.6 = 0.002794
CNY 0.003050
Latency10.24801657s
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):结合实际案例、背后的设计取舍、分布式系统、以及未来发展趋势、碳中和、under high concurrency、cache strategy、性能优化、关键原理与影响、结合实际案例、服务治理、under high concur",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "在分布式系统中,under high concurrency 的性能优化常以 cache strategy 为第一杠杆,但缓存与数据一致性的矛盾是核心设计取舍。以电商秒杀为例,Redis 缓存热点数据能显著提升 system throughput,但库存扣减需借助 token generation ",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 776,
  "completion_tokens_details": {
    "reasoning_tokens": 618
  },
  "prompt_tokens": 214,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 990
}
Fixes
Created At9/9/2026, 2:31:54 PM