ALL TRANSACTIONS

guudp06NfHVj8v4b

CONSUMP_PREPOST_GRANT

completed · 9/9/2026, 2:32:58 PM

Statuscompleted
Date9/9/2026, 2:32:58 PM
Usersamuel_wang@yeah.net
User AmountCNY 0.0265842
User BalancegudA6ExG30hklCQ2
Vendorvolcengine-bizplan-dtx
Vendor CostCNY -0.0236304
Vendor BalancegtMyXDjqOp6l8OSh
Aliasdeepseek-v4-pro-g3 / gucs9pv3TRoBtepN
Mode / Protoreq-v1-chatcmpl / openai-chatcmpl
Log MIDguudp03O1fwDKLA0
SETTLEMENT TELEMETRY

Inference Log

Log MIDguudp03O1fwDKLA0
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
216 × 4.05 = 0.000875
0 × 0.135 = 0.000000
2116 × 12.15 = 0.0257
CNY 0.0266
Vendor Cost
216 × 3.6 = 0.000778
0 × 0.12 = 0.000000
2116 × 10.8 = 0.0229
CNY 0.0236
Latency41.92904552s
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):分点阐述其中的、并发控制、分点阐述其中的、数据一致性、under high concurrency、the system throughput、关键原理与影响、人工智能、分点阐述其中的、人工智能、背后的设计取舍、streamin",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "在生产环境中,分布式系统承载人工智能/机器学习推理时,under high concurrency 下的并发控制与数据一致性是核心。以 LLM 的 streaming response 和 token generation 为例,通过请求队列、信号量与动态批处理提升 the system throu",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 2116,
  "completion_tokens_details": {
    "reasoning_tokens": 1897
  },
  "prompt_tokens": 216,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 2332
}
Fixes
Created At9/9/2026, 2:32:58 PM