
OpenLLM — All your LLM needs in 1 place
Format-agnostic LLM hub. Bring your own provider keys and route across Anthropic, OpenAI, ChatGPT/Codex, Kimi, Alibaba DashScope, and AWS Bedrock — with unified observability and c
@0xxmemo · X
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Format-agnostic LLM hub. Bring your own provider keys and route across Anthropic, OpenAI, ChatGPT/Codex, Kimi, Alibaba DashScope, and AWS Bedrock — with unified observability and c
@0xxmemo · X

追踪您的应用中使用的 AI 模型,并在其被弃用前获得警告。
taylorgt · HN
Find every AI model your code calls and warn before it's retired

查看LLM模型在10个基准问题上的评分和排名。
fristovic · HN
She watched me look at model rankings and asked what do the numbers mean... I literally had no good way of explaining it to her so I just came up with something that is approximately in the same ballpark as some of the benchmarks out there lol

自动将提示词路由到最便宜的模型,节省API成本。
u/ASDKING100 · Reddit
Launched an AI API router tonight, and found a bug hours in that would've taken real payments without ever upgrading the account Built LLMLite over the past few weeks — it classifies each prompt and routes it to the cheapest model that can actually handle it, instead of hitting GPT-4o for everything. Free tier, no card needed to try it. Tonight, right as I was about to launch, ran a real transaction to test the payment flow end to end. Paddle processed it, webhook fired, signature verified

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

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

检测LLM API是否被降智或偷换模型,一键跑6项探针得出结果
cocodot LLM 降智检测 — 免费的 LLM API「降智/偷换模型」在线检测:填入任意 OpenAI 兼容端点的 base_url 和临时 API Key,跑 6 项探针(模型声明、动态题、能力完整性等)生成分项报告;Key 仅用于当次检测、不落库不留存,检测方法[开源](https://github.com/cocodot2026/cocodot-llmprobe)

追踪100+来源的AI和LLM新闻和模型发布。
jonam21 · HN
KBlip – turns AI/LLM news across 100 sources into daily digest threads

将LLM调用路由到成本最低的合适模型,保持质量。
george_avila · Product Hunt
IQ Routing Trajectory-aware LLM routing that cuts agent cost

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]

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

用对抗测试检查LLM端点安全,获取OWASP审计报告。
@aryaan_sheth · X
- LLM security for small teams