SETTLEMENT TELEMETRY

Inference Log

MID: guue0MUPQ34oNSAQ

Log MIDguue0MUPQ34oNSAQ
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
212 × 4.05 = 0.000859
0 × 0.135 = 0.000000
1701 × 12.15 = 0.0207
CNY 0.0215
Vendor Cost
212 × 3.6 = 0.000763
0 × 0.12 = 0.000000
1701 × 10.8 = 0.0184
CNY 0.0191
Latency34.34151958s
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):机器学习、人工智能、潜在的风险点、latency distribution、算法复杂度、人工智能、云计算架构、并给出可落地的建议、分点阐述其中的、以及未来发展趋势、请举例说明、背后的设计取舍、在生产环境中、人工智能、请详细说明、",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "在生产环境中,机器学习/人工智能服务的核心风险点不是平均延迟,而是 **latency distribution** 的尾部:**under high concurrency** 下,**算法复杂度**高的请求会放大排队效应,导致 p95/p99 恶化。**云计算架构**中的**并发控制**、**l",
    "tool_calls": [],
    "stop_reason": "length"
  }
}
Stop Reasonlength
Token Usage
{
  "completion_tokens": 1701,
  "completion_tokens_details": {
    "reasoning_tokens": 1444
  },
  "prompt_tokens": 212,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 1913
}
Fixes
Created At9/9/2026, 2:33:30 PM