完整作品展
技术栈
18 projects
Access leading discounted AI models from OpenAI, Anthropic, and DeepSeek through one unified API without changing your request format.
@Orbiqen · X
Access GPT, Claude, DeepSeek, and image models from one API. Up to 90% less than official prices on selected models. OpenAI-compatible. Works with Cursor and Claude Code. Try Orbiqen from $1:
开源LLM和视频模型的OpenAI兼容API
bingus-bongo · HN
Use GLM-5.3 in Cursor today via tokengo API
An LLM gateway for OpenAI, Anthropic, Google and Azure. Every request logged, priced to the token, and audited for waste you can actually recover.
@razdagan3 · X
为LLM输出提供token级引文API，通过注意力分析验证。
apoorvumang · HN
TokenPath – token-level citations for LLM output, read from attention
SaaS定价建模和代币成本计算,支持30+种货币的利润分析。
@HelloCalcaas · X
减少提示中的不必要标记，降低Claude、ChatGPT等LLM的API成本。
u/HourRevolutionary666 · Reddit
Solo founder, first SaaS. Honestly not sure how to get from “it works” to “people use it” Okay so here’s where I actually am right now, not the polished version. Spent months building this on my own. It’s an AI/SaaS tool called Token Optimiser that trims unnecessary tokens out of prompts before they hit the model, so you pay less per call without losing what the prompt actually needs. It’s live at https://www.tokenoptimiser.com , I ran it through a proper benchmark to make sure the numbers
Your OpenAI client, a different base URL, a much smaller invoice. Frontier open-source models on a decentralized GPU network.
@runnoclip · X
AI inference service that cuts your token bills by 50-90%
监控和比较您在OpenAI、Claude等AI服务商上的支出。
@J0nasDav1d · X
Celebrate burning tokens
Rightsize OpenAI and Anthropic models. See what drives your AI bill, then validate cost-efficient model changes without rewriting your application.
@SpendLensAI · X
LLM API支出分析仪表板，按模型和环境分类，含优化建议
ATsimbalistov · HN
Show HN: Tracking GenAI cost and endpoint fragility so app teams don't have to
Ornymo通过语义缓存减少LLM查询成本和延迟。
u/ornymo_official · Reddit
how to reduce ai costs there are lots of way to reduce costs but there all complex to setup i know this cause i tried one in production so i built ornymo we cache meaning not the exact string allowing us to give same awnsers thus reducing llm costs and latency check it out at ornymo.com free for a limited time and let me know your feedback submitted by /u/ornymo_official to r/buildinpublic [link] [comments]