实用工具1 month ago
100 Questions — AI Visibility Audit & Benchmark Tool
审计您的品牌在各大AI搜索引擎中的可见性并识别差距。
@kylekane · X
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审计您的品牌在各大AI搜索引擎中的可见性并识别差距。
@kylekane · X
用Sakura基准测试本地编码模型，测量准确性、延迟和吞吐量。
u/Unfair_Association89 · Reddit
I built a reproducible benchmark for local coding models (Ollama, 27 tasks, live leaderboard) ran it on my 8GB card, here's what I found I kept eyeballing "vibes" to decide whether one quant of a coding model was actually better than another on my machine, so I built Sakura to get real numbers instead. What it does: - Points at any Ollama model and runs it through 27 hand-curated tasks: codegen, bugfix, SQL, refactor, systems design, protocol implementation, and terminal-agent episode
在 30 秒内测量 GPU 的真实内存带宽上限，用于本地 AI。
Ar5en1c · HN
Headroom – measure your GPU's true bandwidth ceiling for local AI
A transparent, research-backed benchmark for startup ideas and websites.
@xmangonic · X
发现你的电脑能运行的本地 AI 模型，包含已验证的基准数据。
@Carl0sFelipe · X
Just shipped — a tool that helps you discover which local AI models actually run on your hardware, with community benchmarks, quantization support, and estimated speed. Building in public from here. #BuildingPublic #AIDevelopment #rust #benchmaks #aimodel
提交 LLM 推理优化内核，在专用硬件上进行基准测试并竞争排名。
carsenk · HN
Frontier.fast – Help push the frontier of LLM speed forward
对比 AI 模型在编码任务上的表现,支持成本追踪和 ELO 排名。
@intheworldofai · X
On the World of AI Bench (vibe-coding composite): Claude Fable 5 → 85.2 GPT-5.6-sol → 82.4 kimi-k3 → 81.5 Moonshot’s K3 just walked in and claimed bronze on one of the toughest coding-focused leaderboards out there.
查看和对比主流AI模型的公众意见和基准评分。
u/TasteMysterious5285 · Reddit
I built AI Census, a live field bulletin for how people are actually talking about AI models I’ve been building AI Census, a public “field bulletin” for how people are talking about current AI models. I kept running into the same problem: benchmark tables tell me how a model performs on a test, but not whether people are actually finding it useful, frustrating, reliable, etc. So I built a rolling view from public technical conversations across Reddit, Hacker News, Bluesky, GitHub, and Huggi
在 leaderboard 上按官方基准对比 AI 大模型的性能排名
fcten · V2EX
做了一个大模型 leaderboard 网站 最近一个月 CodeX 疯狂送重置，token 根本用不完，顺手做点东西。 地址：[知行录]( https://leaderboard.cn/) 排行依据主要为模型官方基准测试成绩。非主观排名。 数据会持续更新。如果有点用，欢迎各位 v 友收藏～
在浏览器中运行AI模型基准测试以检测性能回归。
pepperpoppins · HN
Trunchbull, run real models against any benchmark in your browser
跨14个维度分析Python代码，检测违规并提供详细报告。
@KSFirasa · X
Hello! I built a tool that profiles code (python only atm) across 14 dimensions detecting violations and capabilities outputting a full report. A bit more nuanced than "AI-powered insights". Free while in beta. Thank you!
对比多个LLM API提供商的延迟和吞吐量性能。
@QAInsights · X