SETTLEMENT TELEMETRY

Inference Log

MID: guoNqM0YxscbOlAQ

Log MIDguoNqM0YxscbOlAQ
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
286 × 4.05 = 0.001158
0 × 0.135 = 0.000000
2058 × 12.15 = 0.0250
CNY 0.0262
Vendor Cost
286 × 3.6 = 0.001030
0 × 0.12 = 0.000000
2058 × 10.8 = 0.0222
CNY 0.0233
Latency41.10774006s
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):算法复杂度、请详细说明、分布式系统、the system throughput、streaming response、分布式系统、under high concurrency、潜在的风险点、数据一致性、背后的设计取舍、请详细说明",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "在分布式系统中,流式响应(streaming response)在高并发(under high concurrency)下会放大算法复杂度、内存管理与并发控制的影响。以机器学习推理的 token generation 为例,生成阶段的计算复杂度和 cache strategy 直接决定 the sy",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 2058,
  "completion_tokens_details": {
    "reasoning_tokens": 1801
  },
  "prompt_tokens": 286,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 2344
}
Fixes
Created At9/8/2026, 7:42:02 PM