Cursor, since Grok 4.5, has had an incredible deal for frontier level models, their subscription now goes way further than OpenAI or Anthropic. Even on their lower tier plans you can use a lot tokens on their of their first party models (Grok and Composer) and not really run out comparatively. Combine them with an orchestrator and implementor type setup and it goes even further.
I often wonder if there's a chance, even if minimal... that they stole the weights of the Anthropic models they run on their datacenter... or are actively destillating it.
Interesting. Grok 4.5 is a capable model, although not quite at Fable/Sol levels. Will be interesting to see how this holds up. Musk appears to have made a savvy choice buying Cursor's data.
SpaceXAI is the only frontier model company that had its own compute/date centres and soon chip making factory, I think they will pull ahead with cheaper tokens similar intelligence and better harness/tools. Grok build is 2-5x faster than Claude Code in my opinion.
note that Grok's training, thanks to its portable gas generators that are magnitudes less efficient than even other integrated, permanent gas turbines, means the training for this model is dramatically less efficient than models like DeepSeek
a lot of the CO2 emission debate on AI is overblown but it's accurate for Grok
Can someone explain to me what's the point of Grok anymore? I don't understand why we need a third or fourth closed frontier model. It is clear that chatGPT has locked down the consumer play, and may be Gemini is there. Claude has enterprise locked up, followed by chatGPT and Gemini. Enterprise switching costs are notoriously high, and even if they switch, they have chatGPT or Gemini to choose from. Beyond that, you have a vast array of open source models (DeepSeek, Kimi, and now Meta's Spark and Glimmer). So, why would anyone need a third or fourth frontier model and why would SpaceX spends billions in CapEx for a very small market share
That is good news for Grok team. However, most of the time cost comparing to the result is secondary, and better results and conclusions can come from mixing AI brains together.
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[ 0.22 ms ] story [ 17.5 ms ] threadIn my experience in heavy coding sessions most pricing is just cache read and cache write like 80% of my token bill.
Google would like a word. Also, Microsoft.
here's Stanford HAI's graph on the carbon emitted from model training per model:
https://spectrum.ieee.org/media-library/chart-showing-estima...
note that Grok's training, thanks to its portable gas generators that are magnitudes less efficient than even other integrated, permanent gas turbines, means the training for this model is dramatically less efficient than models like DeepSeek
a lot of the CO2 emission debate on AI is overblown but it's accurate for Grok
I used auto in cursor it’s much faster va Claude code and as good.