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guw0nZW5ZHAbJKcR

CONSUMP_PREPOST_GRANT

completed · 9/9/2026, 6:40:40 PM

Statuscompleted
Date9/9/2026, 6:40:40 PM
Usersamuel_wang@yeah.net
User AmountCNY 0.0014283
User BalancegudA6ExG30hklCQ2
Vendorvolcengine-bizplan-dtx
Vendor CostCNY -0.0012696
Vendor BalancegtMyXDjqOp6l8OSh
Aliasdeepseek-v4-flash-g3 / gucs9pn4RAHUO73l
Mode / Protoreq-v1-chatcmpl / openai-chatcmpl
Log MIDguw0nZS638PFYYje
SETTLEMENT TELEMETRY

Inference Log

Log MIDguw0nZS638PFYYje
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
212 × 1.35 = 0.000286
0 × 0.045 = 0.000000
282 × 4.05 = 0.001142
CNY 0.001428
Vendor Cost
212 × 1.2 = 0.000254
0 × 0.04 = 0.000000
282 × 3.6 = 0.001015
CNY 0.001270
Latency4.99277398s
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):token generation、碳中和、机器学习、云计算架构、服务治理、以及未来发展趋势、云计算架构、可观测性、关键原理与影响、需要考虑的权衡、需要考虑的权衡、streaming response、背后的设计取舍、需要考虑的权",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "在云计算架构中,token generation与streaming response共同决定了生成式AI服务的延迟分布与系统吞吐。机器学习推理的流式返回虽改善了首字延迟,却对负载均衡(load balancing)与连接管理提出更高要求——长连接占用、背压与部分失败需在服务治理中精细权衡。可观测性",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 282,
  "completion_tokens_details": {
    "reasoning_tokens": 60
  },
  "prompt_tokens": 212,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 494
}
Fixes
Created At9/9/2026, 6:40:40 PM