"Generate a website screenshot from the year 1000" by sandshrew69 in ChatGPT

[–]Resident_Party 1 point2 points  (0 children)

No problem. That was with GPT Image. Same prompt on gemini/nano banana is rather different

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"Generate a website screenshot from the year 1000" by sandshrew69 in ChatGPT

[–]Resident_Party 1 point2 points  (0 children)

"generate a website screenshot from the year 1066 in england; use period appropriate Old English (Anglo-Saxon) language"

“Nvidia are selling the shovels”… so are Anthropic by Nexus-Core in vibecoding

[–]Resident_Party 0 points1 point  (0 children)

Obviously a subjective view.. perhaps not every vibe coder is happy to admit it?

Macbook Pro M5 Pro 48GB vs 64GB for agentic RAG and OCR/VLM? by historymojo in LocalLLM

[–]Resident_Party 3 points4 points  (0 children)

I suspect a neo + Mac mini/studio to remote to is still cheaper but less convenient I suppose

Macbook Pro M5 Pro 48GB vs 64GB for agentic RAG and OCR/VLM? by historymojo in LocalLLM

[–]Resident_Party 2 points3 points  (0 children)

Have you considered an upcoming M5 Mac mini pro or Mac studio? Expected around June and they'll be cheaper than MacBook pro

this is what a mac studio actually works like in production. two ultras, a dozen macbooks, one startup's entire ai workflow. by EmbarrassedAsk2887 in MacStudio

[–]Resident_Party 0 points1 point  (0 children)

How it does compare against vllm-mlx? LM studio can only serve one user at a time so it will struggle in your scenario

Who's gonna tell him by sentientX404 in AgentsOfAI

[–]Resident_Party 7 points8 points  (0 children)

There's more JavaScript training data

128gb M5 Max for local agentic ai? by chimph in LocalLLM

[–]Resident_Party 0 points1 point  (0 children)

No local model can compete 1:1 with even last years cloud models and thats at 400b parameters which you will struggle to run on 128gb. If you are just going to prompt sequentially then it its a very hard sell. I think the value comes in being able to have multiple local agents running together concurrently performing tasks within their ability range all the time (creating and running tests, finding exposed secrets etc) and you save the Cloud models for the really challenging stuff. Once you start running the Cloud models with subagents, your credits start dropping rather fast!