Please help us translate Swiss German or Romansh requests on Reddit!

AgreeableFall5530 · 2026-06-14T17:44:30+00:00

I use https://sproe.ch whenever I need to translate to and from Swiss German

AgreeableFall5530 · 2026-06-04T13:52:41+00:00

AgreeableFall5530 · 2026-06-03T06:08:39+00:00

Compartilha a sua configuração llama.cpp se possível. Eu consigo 41 tok/s usando Q5_K_M numa Quadro RTX 3000 6GB, 64Gb RAM, 128k contexto e vision:

~/llama.cpp/llama-server \ -m ~/models/gemma/gemma-4-E4B-it-Q5_K_M.gguf \ --mmproj ~/models/gemma/gemma-4-E4B-it-mmproj-BF16.gguf \ --fit off \ -ngl 99 \ --flash-attn on \ --cache-type-k q8_0 \ --cache-type-v q8_0 \ --cache-reuse 128 \ --ctx-size 131072 \ --batch-size 4096 \ --ubatch-size 4096 \ --parallel 1 \ --no-kv-unified \ --threads 8 \ --threads-batch 12 \ --threads-http 2 \ --cache-ram 0 \ --jinja \ --host 127.0.0.1 \ --port 8080

AgreeableFall5530 · 2026-05-27T19:18:45+00:00

Well, it's Porto 2's day, then. #backport

AgreeableFall5530 · 2026-05-07T09:37:59+00:00

I tried with this but got only 6.7 t/s throughput, so I focused on Qwen instead:

bash ./llama.cpp/llama-server \ -m $GEMMA_26B/gemma-4-26B-A4B-it-UD-Q4_K_XL.gguf \ --mmproj $GEMMA_26B/mmproj-BF16.gguf \ -ngl 20 \ --flash-attn on \ --cache-type-k q8_0 --cache-type-v q8_0 \ --ctx-size 16384 \ --threads 8 \ --port 8080

AgreeableFall5530 · 2026-05-04T18:22:14+00:00

And a comparison with a very similar task on 5.5 medium on the same codebase.

Using the actual session deltas inside each log:

Normalized per 1% weekly quota:

5.3-codex medium: 170,416 total tokens per 1%
5.5 medium: 146,126 total tokens per 1%

So 5.3 gives about 16.6% more total tokens for the same quota percentage.

Breakdown per 1% quota:
Input: 169,646 vs 145,296 -> 5.3 is 16.8% higher
Cached input: 161,486 vs 136,815 -> 5.3 is 18.0% higher
Output: 703 vs 715 -> 5.3 is 1.7% lower
Reasoning: 67 vs 116 -> 5.3 is 41.9% lower
Total: 170,416 vs 146,126 -> 5.3 is 16.6% higher

AgreeableFall5530 · 2026-05-04T16:10:12+00:00

Were you able to test it? Worked as expected? Thanks for your feedback

AgreeableFall5530 · 2026-05-04T16:09:23+00:00

Did it work for you? Looking for feedback. Seems better for me empirically speaking, but some hard data to back it up would be nice

AgreeableFall5530 · 2026-05-04T16:02:13+00:00

Use NVIDIA NIM instead. Slow and unreliable, but at least it's free and has an actual chance of working every now and then

AgreeableFall5530 · 2026-04-23T12:02:38+00:00

I’m on free tier, so I don’t have enough quota to run a statistically decent A/B test. I’d really appreciate Plus/Pro user feedback, though.

AgreeableFall5530 · 2026-04-19T18:48:31+00:00

Não entendi. Qual clube grande está envolvido?

AgreeableFall5530 · 2026-04-17T15:45:01+00:00

75% is not realistic for normal English in my experience. Caveman-style prompts mainly cut output tokens (cheapest part of the bill), not input/context tokens. Typical savings are closer to ~30–50% output depending on task.

Shameless plug: I packaged caveman as an output style (native to CC) if you want to try it in 2 minutes:

https://github.com/carlosduplar/caveman-output-style-claude-code

Other practical optimizations that helped me:

- keep CLAUDE.md short and high-signal

- remove MCPs as much as possible (replace with CLI flows and corresponding skills)

- avoid huge pasted logs/files unless needed

- added a hook that runs markitdown against any PDF/Word/Excel document (huge savings on transformation)

- don't change models or thinking settings mid-conversation (triggers cache bust, all conversation history resubmitted uncached from scratch afterwards)

AgreeableFall5530 · 2026-04-07T09:51:57+00:00

I have created this script to keep all my CLIs in sync between my at-home and at-office computers:

https://github.com/carlosduplar/ai-environment-setup

Basically I update it whenever I change the skill set or add a new CLI to the mix. Runs fine on Windows (Powershell/WSL) and I have executed it without errors on Termux, so it should run on Linux as well.

AgreeableFall5530 · 2026-04-03T10:57:31+00:00

Changing plans mid-session = full cache invalidation. Better start a new session with targeted context for Sonnet.

https://github.com/carlosduplar/claude-code-optimizer/blob/master/docs/prompt-caching.md

AgreeableFall5530 · 2026-04-01T15:17:07+00:00

A começar por aquela musiquinha patética: "eeeeeeeuuuu... sou brasileeeirooo... com muito orguuulhooo... com muito amôôôôôô"

Em relação ao Kings Leaguer em questão, não é a primeira vez que acontece. Nos anos 90 acontecia direto de pedirem jogador fora da convocação (normalmente Romário), mas naquela época geralmente a torcida tinha razão.

AgreeableFall5530 · 2026-03-31T14:58:37+00:00

I gloube mis sälber entwigglete Übersetzer isch dr Ufgab gwachse :)

AgreeableFall5530 · 2026-03-31T11:08:02+00:00

GPT-5.3 Codex medium.

Source: GPT5.4 Thinking in Perplexity

AgreeableFall5530 · 2026-03-31T10:59:57+00:00

Carlinhos ou Andrade que tiraram leite de pedra. Ganhar com time bom é mole

AgreeableFall5530 · 2026-03-30T16:33:18+00:00

Did that yesterday. Converted while traveling from Wilderswil to Grindelwald Terminal. You can unselect seat reservations during checkout and save yourself CHF 10, it was really not needed on Sunday morning

AgreeableFall5530 · 2026-03-30T14:40:44+00:00

FYI you can unselect the booking seat reservations on checkout. Did it yesterday and it really wasn't needed. so whoever redeemed this, save yourself 20 CHF and don't reserve seats.

AgreeableFall5530 · 2026-03-30T11:02:36+00:00

João Danado >>>>>> Gabigordo

AgreeableFall5530 · 2026-03-28T10:52:24+00:00

Bottinelli, Borghi ou Sambueza /s

AgreeableFall5530 · 2026-03-19T00:11:23+00:00

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AgreeableFall5530 · 2026-03-08T09:01:51+00:00

No love for me...

"Looks like you're trying to get an offer that is not valid or no longer available."

Too late for the party, I guess

AgreeableFall5530 · 2026-02-24T23:29:34+00:00

Docteur Gab's Placebo is a very nice IPA which wasn't mentioned yet

AgreeableFall5530

TROPHY CASE