High treason, I'm afraid. You'll swing for that.

I don't understand. So, if VLC was downloaded from Tucows or GitHub...who pays? Surely not VLC, because as I read it, this taxes "producers of digital data" but the measurement mechanism is ISPs counting bytes by sender IP.

So if a French user downloads VLC from Tucows, Sourceforge, or Akamai's CDN, the bytes come from Tucows/Akamai's IP, not VideoLAN's. Under a strict sender-IP reading, Tucows pays, not VideoLAN.

Wat?

If in some crazy world this actually goes ahead as written, one of two things happen

1. Everyone on earth geoblocks French IPs
2. Everyone dumps everything onto mirrors and washes their hands of it.

Impossible to say. The token use difference between instant (nigh on useless,) and medium or high (what people anecdotally default to) could be significant.

Eg: if we consider GLM 5.3, the difference in token use between reasoning none and reasoning high is about 3x

https://artificialanalysis.ai/models/comparisons/glm-5-3-low-vs-glm-5-3

But without access to actual token consumption figures, comparing the old and new usage allowances is difficult. Suffice it to say it's unlikely to be in your favour.

The curse and blessing of unified memory!

I was considering getting a BC-250 (a cut down PS5) with 16GB unified memory, but at 400GB/s bandwidth.

When they were cheap, it almost made sense. But realistically, I can get similar speeds with a MoE thanks to cpu and system ram, and 16GB is just not enough for anything top shelf (no, Prism MLs Bonsai models don't count. I don't care what the benchmarks say - they're lobotomised).

Still, given the chance to get a Strix on the cheap, I'd go for it. There's something very nice about a low power box that can run a 120B model at speed.

A Strix. In 2026. Must be nice :)

It's a two pronged attack for sure. Make local expensive, make cloud worse.

I think there's still some wiggle room to be had in the 8 to 16GB VRAM range...so I'm hoping Qwen 4 series brings its A game.

Enjoy and good luck!

It's something you'll probably download directly from HuggingFace. That is - people will de-censor models and you just download them.

Of course, you can grab the tools and de-censor your own. It's a bit of a black art tho; I abliterated a Qwen3.5-2B once (I thought quite well, actually; minimal damage 0.0006)...only to have BADLY ruined its tool calling abilities.

Leave it to the known good quantizers over on HuggingFace.

Copyright infringement for me, not for thee, eh Claude?

Nvm. GLM5.3 is just as good...and a good deal more slutty about this sort of stuff :)

Friends don't let friends use Ollama

If you want a gentle start, may I suggest Jan.ai? It's a ride on lawn mower compared to the sports car I suggested...but you need to dip your toe into the water before you go ludicrous speed.

Once you get a feel for that, I'm going to suggest some MCP tools to you as well. I don't know if Jan finally added MCP servers to their stack (they should have by now!).

The following are ... ok. Not the best and not what I run with but again, lawn mower before sports car

https://github.com/ofershap/mcp-server-markdown

https://github.com/jeffreyrampineda/kiwix-wiki-mcp-server

https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem

https://github.com/exa-labs/exa-mcp-server

https://exa.ai/

https://www.home-assistant.io/integrations/mcp_server/

Sorry - again: too much info. Start with Jan. You'll be amazed...and then perplexed...and then frustrated. That's the time to migrate thru to llama.cpp or PolyStrata and start adding those MCP tools I mentioned above.

https://github.com/VecSzn/PolyStrata

https://github.com/srware-net/LocalLightChat/

https://github.com/open-webui/open-webui

Then we can get freaky :) Oh...we have such sights to show you lol

Depends what your interests are! I can get around 35ish tok/s TG at - c 48,000 of Qwen 3.6-35B-A3B (Q4_K_M) using polystrata on a similar rig (you've got an A1000, I have a T1000).

Which means absolutely nothing to you right now but suffice to say - Polystrata + Qwen 35B is something to try. It's among the "smartest" you can run on your rig.

Personally, for every day use, I like Ling 3.0 Tiny at Q6 or SharpMiniCPM5-2B at Q8. They are stupidly fast, and supported by MCP tools and a bridge I wrote, work as excellent "hey, I'm thinking of X. Can you tell me about it? And what about Y and Z?" or "How does this read?".

I pull out my phone, send them a text message and they text me back.

Think of it like a Google in your pocket, except off line (unless you tell it to go online). Which technically I suppose makes it agentic lol.

(I can show you some examples if you'd like. I keep a set list of 8 tasks I use for benchmarking as I tweak things, as well as some off the wall / out of band queries)

Being that Ling or CPM only take up a sliver of the GPU, I can run them concurrently with other models (like an image generator, text to speech, vision etc) to create a really useful offline house brain, that can roam across my local documents, offline wikipedia (Kiwix) and the like.

It's the combination of things that results in a 1+1=3

Having said that, my AI ladder is

• 90% Ling or minicpm5
• 9% Qwen 3.6-35B
• 1% GLM5.3 Flash via open router.. which costs fractions of a cent for what I need (there are tricks to this but it's probably out of scope to info dump it on you at this stage).

For now, I keep a $20 ChatGPT Plus (separate pools for chat and Codex have been so good) but I am ditching that asap, with the changes coming this month.

HTH. Write back if you need anything else. It's nice to see someone else rocking an A1000 / T1000. Your rig should be significantly faster than mine... which is why the A1000 is still stupidly expensive for a 50W card.

EDIT: just saw you said "CPU is i7-12700". With that RAM, that CPU and that GPU, I'd guess you'll hit 50-60 tok /s with Qwen 3.6-35B using polystrata once you get the GPU / CPU split right.

In other words, congrats and go fuck yourself :) You have a very nice little inference box. And yes, it can do your calendar alerts thing.

I personally use RedReader (signed out) and "share to" Linkora to save useful threads.

https://f-droid.org/packages/org.quantumbadger.redreader/

https://f-droid.org/packages/com.sakethh.linkora/

That works for now. If redreader stops working... 🤷 bye Felicia. I don't visit Reddit much anyway.

I've replaced "sitting at PC, nothing to read" with neal.fun, Atlas Obscura, Smithsonian Smart News and Lemmy 🤣

PS: IIRC, you can download a good chunk of reddit as an archive to search against.

https://github.com/ArthurHeitmann/arctic_shift

https://github.com/19-84/redd-archiver

I think the full pushshift reddit archive (to 2024?) was 4TB, but you can just grab smaller useful subsections. So it's less of a workaround and more a "tube is out of the toothpaste, suck shit Spez".

Actually, redd-archive (which is up to end of 2025) has an MCP, so you could point your local LLM at it and get it to find the info you need, all off line.

Last I checked, it even let you grab snapshots of particular subreddits of your choice, so you're not grabbing multiple terabytes. 2026 snapshots aren't out yet IIRC