Seedream 5.0 Pro — 多模型 AI 图片工作台，支持文字生图、图片生图、复杂布局与多语言文字编辑

davidtsong · HN

Benchmarklist: track AI benchmarks (2.4k+), models, and capabilities

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～

bnfcl · HN

What's AI's go-to, public or private healthcare?

adam_rida · HN

Echo – Fable-level results at 1/3 the cost using open-weight models

@nodeloc_cc · X

🌈 7月，你好，MODELOC上线算力池。 MODELOC自上线以来，已检测2000余次，覆盖600+中转站，为众多AI用户提供的使用参考。 MODELOC近期进行了改版，上线了算力池及市场。 加入算力池 查看帖子： 用 MODELOC 便宜地调各家大模型：一次讲清它的价格体系

cdnsteve · HN

Tokenstead, find AI models for your hardware

@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.

fran-mora · HN

I gave 5 AI coding agents one prompt: grow a banana plant through its whole life in three.js: sprout, leaves, flower, fruit, rot, then pups that restart the loop. It's deceptively simple and yet very hard to get right from procedural code: you have to write working three.js and understand how the plant is actually built; how it hangs, ages and decays. Get the biology wrong and the code renders something weird. These are agents, not bare models (Claude Code and Codex for now). They can use tools, including playwright to check their work and improve it.

orion1 · V2EX

vibe conding 撸了两个工具。 都是自己经常再用的 1 ，翻译站，模仿的 deepl ，主要是翻译网站只给一个翻译，有的时候未必是自己想要的那个，这个能调用多个模型都翻译一遍。 https://translate.v8ce.com/ 2 ，音视频处理工具，不上传数据，只调用浏览器能力。有的时候想简单裁切一下视频，压缩或者加速，打开大型处理软件有点太重了。 https://video-tools.v8ce.com/

u/trekhleb · Reddit

I kept pasting the same question into ChatGPT, Claude, and Gemini in three tabs; so I built a Yes-Brainer — a council of AI models, that answer your question in parallel, debate to consensus, or get judged to a verdict. submitted by /u/trekhleb to r/SideProject [link] [comments]

@MBrew26730 · X

Dataset cleaning + fine tuning + continual learning at