ALL TRANSACTIONS
guoJ8ccTuYbAdodx
CONSUMP_PREPOST_GRANT
completed · 9/8/2026, 7:28:19 PM
Statuscompleted
Date9/8/2026, 7:28:19 PM
Usersamuel_wang@yeah.net
User AmountCNY 0.02210085
User BalancegudA6ExG30hklCQ2
Vendorvolcengine-bizplan-dtx
Vendor CostCNY -0.0196452
Vendor BalancegtMyXDjqOp6l8OSh
Aliasdeepseek-v4-pro-g3 / gucs9pv3TRoBtepN
Mode / Protoreq-v1-chatcmpl / openai-chatcmpl
Log MIDguoJ8cWUdLS90eom
SETTLEMENT TELEMETRY
Inference Log
Log MIDguoJ8cWUdLS90eom
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
288 × 4.05 = 0.001166
0 × 0.135 = 0.000000
1723 × 12.15 = 0.0209
CNY 0.0221
Vendor Cost
288 × 3.6 = 0.001037
0 × 0.12 = 0.000000
1723 × 10.8 = 0.0186
CNY 0.0196
Latency30.73735240s
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):碳中和、under high concurrency、服务治理、并给出可落地的建议、内存管理、latency distribution、cache strategy、在生产环境中、load balancing、潜在的风险点、st",
"has_image": false,
"has_tool_result": false
},
"assistant_summary": {
"text": "在“碳中和”目标下,生产环境中的 AI token generation 服务在高并发场景中要平衡系统吞吐、延迟分布与能耗,核心是在服务治理、内存管理和缓存策略上做设计取舍。分布式系统中通过负载均衡将请求按模型副本、GPU 显存和队列深度分配,并用并发控制做请求准入,避免过载。内存管理需限制 KV ",
"tool_calls": [],
"stop_reason": "stop"
}
}Stop Reasonstop
Token Usage
{
"completion_tokens": 1723,
"completion_tokens_details": {
"reasoning_tokens": 1407
},
"prompt_tokens": 288,
"prompt_tokens_details": {
"cached_tokens": 0
},
"total_tokens": 2011
}Fixes
Created At9/8/2026, 7:28:19 PM
TRANSACTION DETAILS