Chubby♨️@kimmonismus · 5月15日63I've been testing Higgsfield's Supercomputer for the past few days, and it genuinely caught me off guard.
You type a task in plain language. The system picks from 61 production skills, routes each sub-task to the best available model (GPT-5.5, Claude Opus, Gemini, Seedance, Veo, Kling, and more), runs them in parallel, and delivers finished assets.
I pointed it at my own X post analytics, expecting something generic.
It came back with senior-analyst-grade breakdowns: median engagement rates, hook score analysis, content pattern detection.
Properly useful output, not a summary paragraph.
A few things that really surprised me:
- It generates up to 60 (!) minutes of video from a single prompt
- Native Obsidian integration for persistent knowledge (the "LLM wiki" concept Karpathy floated recently, already shipping, and which I was building myself just recently)
- 27 platform connectors (Slack, Drive, Notion, YouTube, Frame. io, the full stack)
- Brand and identity locks persist across sessions, so your outputs stay consistent over time
- Skills actually improve with use, version-tracked and eval-tested
The whole thing runs cloud-side on GPU-colocated infrastructure, which means generations keep running even if you close the browser. Scheduled tasks just work without a local machine.
译Higgsfield的Supercomputer平台允许用户以自然语言描述任务,系统从61种生产技能中自动选取,并将子任务路由至GPT-4o、Claude Opus、Gemini及多种图像视频模型并行处理。它能生成长达60分钟的视频,原生集成Obsidian构建持久化知识库,并通过27个平台连接器连接各类工具。平台运行于云端GPU基础设施,支持品牌标识锁定和后台任务调度。其技能在使用中通过版本追踪和评估测试不断自我改进,用户可通过浏览器或Telegram直接访问,无需本地设置。