
LGTM: Vibe Coding Brain Rot Test
每日解谜游戏,找出AI生成代码片段中的错误并跟踪分数。
@MinnerAlgo · X
spun this app up yesterday. it’s like wordle (everyone has same problem to solve each day) for battling vibe coding brain rot. y'all still got it or are you cooked already?
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每日解谜游戏,找出AI生成代码片段中的错误并跟踪分数。
@MinnerAlgo · X
spun this app up yesterday. it’s like wordle (everyone has same problem to solve each day) for battling vibe coding brain rot. y'all still got it or are you cooked already?

估算LLM推理所需的显存、延迟、TTFT、TPOT与吞吐量。
popopanda · HN
LLM Inference Calculator – Estimate VRAM, Latency, and Throughput

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

追踪你的面试过程,获得AI驱动的反馈来发现失去offer的原因。
@anujmenta · X
Building — interview tracker + AI coach for SWE job seekers. Know exactly where you’re losing offers.

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

计算LLM微调和推理所需的GPU显存。
@FaiqAdzlan · X
Built a GPU VRAM calculator to try out Claude Code (#cursorfanboy). I wanted it as granular as possible so I based it off of LLMem) which really just covers fine-tuning tbh. Please tear it to shreds: GitHub:

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

AI生成GitHub开发者的幽默评论。
hito20 · HN
I built an AI that roasts GitHub profiles

Convert PDF, DOCX, XLSX, CSV, JSON, XML, HTML, Images to clean Markdown optimized for AI Agents, RAG, and Vector DBs. 100% Privacy-First, In-Browser Conversion.
@13SahajChawla · X
For professionals to redact their client's sensitive informations before giving AI to process it & while converting any kind of document to a structured MD file. Better quality outputs, 100% privacy with on-browser local processing, and fully free!


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