开发者工具1 month ago
Auriko | One API for Every LLM, Zero Markup, Cache-Aware Cost Arbitrage
使用一个 API 访问和切换多个 LLM 提供商，同时优化推理成本。
justin2025 · Product Hunt
Auriko Trading desk for LLM calls
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使用一个 API 访问和切换多个 LLM 提供商，同时优化推理成本。
justin2025 · Product Hunt
Auriko Trading desk for LLM calls
计算应用栈何时超出AI、托管、数据库等免费层。
@K_dev001 · X
Vibe coding makes launching an app almost free. Running it is another story. I built to calculate your full AI + app stack costs and show which free tier breaks first. Sourced pricing. No signup. No guessing. ->
压缩提示词并检测重复工具调用，降低LLM代币成本
@DeveloperL92487 · X
I built my first app in 60min And now I got $500 MRR in one month Check here if you are interested It’s a tool to reduce agent token consumption, speed up agent response, and clean up memory cache
用免费计算器估算抵押贷款、汽车贷款和个人贷款的月付款——无需注册
@itskdubs_ · X
BizCalc：32+个免费商业计算器，用于计算利润率、损益平衡和自雇税费。
@BizCalcLab · X
RealCalculators 提供 48 个免费在线计算器，涵盖财务、健康、数学和日常需求。
@avinashraj61815 · X
i vibe coded this week
Calculate SIP & lumpsum mutual fund returns with LTCG/STCG tax in seconds. Free forever. No ads. Covers equity, debt & hybrid funds. Built for Indian investors.
@RahulGupta8999 · X
Just shipped 🚀 Free SIP & lumpsum calculator for Indian investors with actual LTCG/STCG tax breakdown. No ads. No sign-up. Forever free. Would love your feedback! 🙏🇮🇳 #BuildInPublic #MutualFunds #SIP
用 470+ 个免费财务计算器计算抵押贷款、税收和退休。
@AfridiMunir · X
计算抵押贷款、贷款、税款和储蓄的在线计算器
@darsh0891 · X
Meet CalcyFinance — the simple way to track your budgets, monitor spending, hand actually hit your savings goals without the headache. Stop guessing where your money goes. Try it out: 👍 #PersonalFinance #Budgeting #Fintech #buildinpublic
输入收入、支出和资产获得财务健康评分及个性化改进计划。
@grademyfinance · X
使用97个免费财务计算器计算抵押贷款、退休、税收和债务。
@finexplainedhq · X
向多个前沿大模型提问，获得经过同行评审的综合答案。
u/Puzzleheaded-Log-27 · Reddit
Building a multi-model AI deliberation tool taught me something about trust LLM Counsel isn't another wrapper around one model - it sends your question to a panel of frontier LLMs, has them peer-review each other anonymously, and an impartial "chairman" model returns one synthesized answer. Free to start, pay-as-you-go after, credits don't expire. What I've learned so far: people trust a synthesized answer a lot more once they can see that the models actually disagreed and how that disagree