Google is already doing that since last year and the models where never leaked, so I don't think that would even be a problem. https://cloud.google.com/blog/topics/hybrid-cloud/gemini-is-...
Are you also talking about personal projects? That wouldn't be enough for me for work either, but for personal use, my $20 Codex subscription is perfectly fine. Then again, as a new dad, I can maybe only work on…
There Seen to be more and more harness benchmarks out there, pretty interesting read: https://neuralnoise.com/2026/harness-bench-wip/
I don't think so, I use GrapheneOS and I think I can't even use the USB-C port for anything other than charging (which should be configurable).
I would assume that if a tool is there and the alternative too costly that they would use the tool instead of buring their project. Just today I stumbled over this for example, where they use GenAI as well:…
Not for coding, but today I stumbled upon these two building their passion project using GenAI, which would otherwise perhaps not be possible: https://reddit.com/comments/1prqfsu
It doesn't have to be hyped to be used, for example today I found these two building their passion project using GenAI, which would otherwise maybe not possible, who knows: https://reddit.com/comments/1prqfsu
This is just one example, but today I found this where two people build their passion project using GenAI for image generation (+ photoshop), maybe otherwise this project wouldn't even be possible:…
Though this Codex version isnt on the leaderboard, GPT-5.2-Medium already seems to be a bit better than Opus 4.5: https://swe-rebench.com/
Your experience seems to match the recent results from swe-rebench: https://swe-rebench.com/
According to SWE-Rebench Anthropic and OpenAI are really close in performance, while GPT-5.2 costs less than half the cost of CC per problem. https://swe-rebench.com/
Interesting. So similar to the vision encoder + projector in VLMs?
I am eagerly awaiting swe-rebench results for November with all the new models: https://swe-rebench.com/
I like this one: https://swe-rebench.com/
Or use RL to beat any AI detectors: https://reddit.com/r/LocalLLaMA/comments/1lnrd1t/you_can_jus...
https://arxiv.org/abs/2311.13600 https://arxiv.org/abs/2410.22911 https://arxiv.org/abs/2409.16167
Thank you for testing, I will test GPT-OSS for my use case as well. If you're interested I have 8 GB VRAM, 32 GB RAM and get around 21 token/s with tensor offloading, I would assume that your setup should be even faster…
Google is already doing that since last year and the models where never leaked, so I don't think that would even be a problem. https://cloud.google.com/blog/topics/hybrid-cloud/gemini-is-...
Are you also talking about personal projects? That wouldn't be enough for me for work either, but for personal use, my $20 Codex subscription is perfectly fine. Then again, as a new dad, I can maybe only work on…
There Seen to be more and more harness benchmarks out there, pretty interesting read: https://neuralnoise.com/2026/harness-bench-wip/
I don't think so, I use GrapheneOS and I think I can't even use the USB-C port for anything other than charging (which should be configurable).
I would assume that if a tool is there and the alternative too costly that they would use the tool instead of buring their project. Just today I stumbled over this for example, where they use GenAI as well:…
Not for coding, but today I stumbled upon these two building their passion project using GenAI, which would otherwise perhaps not be possible: https://reddit.com/comments/1prqfsu
It doesn't have to be hyped to be used, for example today I found these two building their passion project using GenAI, which would otherwise maybe not possible, who knows: https://reddit.com/comments/1prqfsu
This is just one example, but today I found this where two people build their passion project using GenAI for image generation (+ photoshop), maybe otherwise this project wouldn't even be possible:…
Though this Codex version isnt on the leaderboard, GPT-5.2-Medium already seems to be a bit better than Opus 4.5: https://swe-rebench.com/
Your experience seems to match the recent results from swe-rebench: https://swe-rebench.com/
According to SWE-Rebench Anthropic and OpenAI are really close in performance, while GPT-5.2 costs less than half the cost of CC per problem. https://swe-rebench.com/
Interesting. So similar to the vision encoder + projector in VLMs?
I am eagerly awaiting swe-rebench results for November with all the new models: https://swe-rebench.com/
I like this one: https://swe-rebench.com/
Or use RL to beat any AI detectors: https://reddit.com/r/LocalLLaMA/comments/1lnrd1t/you_can_jus...
https://arxiv.org/abs/2311.13600 https://arxiv.org/abs/2410.22911 https://arxiv.org/abs/2409.16167
Thank you for testing, I will test GPT-OSS for my use case as well. If you're interested I have 8 GB VRAM, 32 GB RAM and get around 21 token/s with tensor offloading, I would assume that your setup should be even faster…