https://review.lineageos.org/c/LineageOS/android_frameworks_...
> this knockoff site shows SHRDLU[1] has the same thing for $40? Person: Grasp the knockoff. Computer: I DON'T UNDERSTAND WHICH KNOCKOFF YOU MEAN. [1]: https://en.wikipedia.org/wiki/SHRDLU
Not, in fact, optical interferometry :(
What's the app data backup/restore story on GrapheneOS? My understanding is that even with pseudo-D2D (device-to-device) transfers Seedvault doesn't backup everything[1]. Are there more-functional, non-root, local…
C binding: [0] [0]: https://github.com/n0-computer/iroh-c-ffi
> Einstein How are you handling relativistic effects in the N-body simulation?
> KeepassXC can't do auto-type on Wayland https://github.com/keepassxreboot/keepassxc/issues/2281 Though it looks like there's a recent PR for that: https://github.com/keepassxreboot/keepassxc/pull/13359
They ever get around to re-adding C++ support?
Prompt processing is absolutely punishing: ./llama-batched-bench -hf unsloth/Qwen3.5-122B-A10B-GGUF:UD-IQ4_NL -npp 1000 -ntg 128 -npl 1 --cache-type-k q8_0 --cache-type-v q8_0 -c 18000 --n-cpu-moe 32 | PP | TG | B |…
Getting ~36-33 tok/s (see the "S_TG t/s" column) on a 24GB Radeon RX 7900 XTX using llama.cpp's Vulkan backend: $ llama-server --version version: 8851 (e365e658f) $ llama-batched-bench -hf…
Hear, hear!
llama.cpp (b8642) auto-fits ~200k context on this 24GB RX 7900 XTX & it shows a solid 100+ tok/s ("S_TG t/s") on the first 32k of it, nice! ./llama-batched-bench -hf unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q4_K_XL \ -npp…
Doesn't seem to serve rendered samples so you have to set "browser.display.use_document_fonts" to "1" to see anything useful.
600 GB/s of memory bandwidth isn't anything to sneeze at. ~$1000 for the Pro B70, if Microcenter is to be believed: https://www.microcenter.com/product/709007/intel-arc-pro-b70...…
Not to be confused with GNU parallel[1], written in Perl. [1]: https://en.wikipedia.org/wiki/GNU_parallel
Speculative decoding[1]? [1]: https://github.com/ggml-org/llama.cpp/blob/master/docs/specu...
> A social networking system simulates a user using a language model trained using training data generated from user interactions performed by that user Google People[1]? [1]: https://qntm.org/perso
> "A system's purpose is what it does" POSIWID: https://en.wikipedia.org/wiki/The_purpose_of_a_system_is_wha...
https://www.redblobgames.com/articles/curved-paths/
Nifty, thanks for the heads-up!
Nice! Getting ~39 tok/s @ ~60% GPU util. (~170W out of 303W per nvtop). System info: $ ./llama-server --version ggml_vulkan: Found 1 Vulkan devices: ggml_vulkan: 0 = Radeon RX 7900 XTX (RADV NAVI31) (radv) | uma: 0 |…
> ConnectBot https://f-droid.org/en/packages/org.connectbot/ https://github.com/connectbot/connectbot
Because TFA never bothered to define it: Broadband Network Gateway (BNG)[1] [1]: https://github.com/codelaboratoryltd/bng#bng-broadband-netwo...
tap tap tap tap tap
Getting ~150 tok/s on an empty context with a 24 GB 7900XTX via llama.cpp's Vukan backend.
https://review.lineageos.org/c/LineageOS/android_frameworks_...
> this knockoff site shows SHRDLU[1] has the same thing for $40? Person: Grasp the knockoff. Computer: I DON'T UNDERSTAND WHICH KNOCKOFF YOU MEAN. [1]: https://en.wikipedia.org/wiki/SHRDLU
Not, in fact, optical interferometry :(
What's the app data backup/restore story on GrapheneOS? My understanding is that even with pseudo-D2D (device-to-device) transfers Seedvault doesn't backup everything[1]. Are there more-functional, non-root, local…
C binding: [0] [0]: https://github.com/n0-computer/iroh-c-ffi
> Einstein How are you handling relativistic effects in the N-body simulation?
> KeepassXC can't do auto-type on Wayland https://github.com/keepassxreboot/keepassxc/issues/2281 Though it looks like there's a recent PR for that: https://github.com/keepassxreboot/keepassxc/pull/13359
They ever get around to re-adding C++ support?
Prompt processing is absolutely punishing: ./llama-batched-bench -hf unsloth/Qwen3.5-122B-A10B-GGUF:UD-IQ4_NL -npp 1000 -ntg 128 -npl 1 --cache-type-k q8_0 --cache-type-v q8_0 -c 18000 --n-cpu-moe 32 | PP | TG | B |…
Getting ~36-33 tok/s (see the "S_TG t/s" column) on a 24GB Radeon RX 7900 XTX using llama.cpp's Vulkan backend: $ llama-server --version version: 8851 (e365e658f) $ llama-batched-bench -hf…
Hear, hear!
llama.cpp (b8642) auto-fits ~200k context on this 24GB RX 7900 XTX & it shows a solid 100+ tok/s ("S_TG t/s") on the first 32k of it, nice! ./llama-batched-bench -hf unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q4_K_XL \ -npp…
Doesn't seem to serve rendered samples so you have to set "browser.display.use_document_fonts" to "1" to see anything useful.
600 GB/s of memory bandwidth isn't anything to sneeze at. ~$1000 for the Pro B70, if Microcenter is to be believed: https://www.microcenter.com/product/709007/intel-arc-pro-b70...…
Not to be confused with GNU parallel[1], written in Perl. [1]: https://en.wikipedia.org/wiki/GNU_parallel
Speculative decoding[1]? [1]: https://github.com/ggml-org/llama.cpp/blob/master/docs/specu...
> A social networking system simulates a user using a language model trained using training data generated from user interactions performed by that user Google People[1]? [1]: https://qntm.org/perso
> "A system's purpose is what it does" POSIWID: https://en.wikipedia.org/wiki/The_purpose_of_a_system_is_wha...
https://www.redblobgames.com/articles/curved-paths/
Nifty, thanks for the heads-up!
Nice! Getting ~39 tok/s @ ~60% GPU util. (~170W out of 303W per nvtop). System info: $ ./llama-server --version ggml_vulkan: Found 1 Vulkan devices: ggml_vulkan: 0 = Radeon RX 7900 XTX (RADV NAVI31) (radv) | uma: 0 |…
> ConnectBot https://f-droid.org/en/packages/org.connectbot/ https://github.com/connectbot/connectbot
Because TFA never bothered to define it: Broadband Network Gateway (BNG)[1] [1]: https://github.com/codelaboratoryltd/bng#bng-broadband-netwo...
tap tap tap tap tap
Getting ~150 tok/s on an empty context with a 24 GB 7900XTX via llama.cpp's Vukan backend.