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
TRANSACTION DETAILS