SETTLEMENT TELEMETRY

Inference Log

MID: guw1NgkdFUqG8ORF

Log MIDguw1NgkdFUqG8ORF
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
217 × 4.05 = 0.000879
0 × 0.135 = 0.000000
2235 × 12.15 = 0.0272
CNY 0.0280
Vendor Cost
217 × 3.6 = 0.000781
0 × 0.12 = 0.000000
2235 × 10.8 = 0.0241
CNY 0.0249
Latency37.06623013s
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):需要考虑的权衡、load balancing、cache strategy、碳中和、潜在的风险点、latency distribution、内存管理、load balancing、需要考虑的权衡、在生产环境中、碳中和、分点阐述其",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "从技术角度分析,人工智能 token generation 在生产环境 under high concurrency 下,背后的设计取舍集中在数据一致性、内存管理与性能优化之间。Load balancing 与 cache strategy 需要结合 latency distribution 动态调",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 2235,
  "completion_tokens_details": {
    "reasoning_tokens": 2037
  },
  "prompt_tokens": 217,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 2452
}
Fixes
Created At9/9/2026, 6:42:22 PM