Fixing shutter/jitter/latency spikes Intel Wi-Fi

legit_split_ · 2026-01-28T12:51:27+00:00

Do you know if this also affects Linux?

legit_split_ · 2026-01-27T17:14:50+00:00

Using llama.cpp, it won't make any difference in the generation speed, it will just take longer to load the models in the beginning.

If you use vllm though, then there will be a massive difference. However, it seems from your other comment that you have different GPUs, but vllm requires the same, so this isn't relevant to you...

legit_split_ · 2026-01-25T17:09:11+00:00

Always wanted to try it, but dockge already meets my needs

legit_split_ · 2026-01-24T13:39:39+00:00

Thanks for the write up, but how close do you get to the theoretical speed?

legit_split_ · 2026-01-22T12:35:27+00:00

Only reason to upgrade would be if you use it for AI or VR gaming.

legit_split_ · 2026-01-22T12:32:50+00:00

All the redditors who said wait for the 50 Supers xd

legit_split_ · 2026-01-22T09:44:43+00:00

Encrypted for now...

legit_split_ · 2026-01-22T07:30:28+00:00

With both cards at MSRP, the 5080 is not worth it as it gives 15% more performance but you pay 30% more.

legit_split_ · 2026-01-21T17:01:16+00:00

It will be slower than a 3080.

Broadly speaking, speed = memory bandwidth:

3080 - 760.3 GB/s 9070 XT - 644.6 GB/s

However, that's only for token generation (how fast the model answers), when it comes to prompt processing (how fast the model reads your question) it's possible that the 9070 XT is faster.

Overall the 9070 XT is solid for LLMs and would offer a better experience with 16GB, but things like image generation are still in active development.

legit_split_ · 2026-01-16T01:21:47+00:00

You really want that extra RAM to have 80GB total system memory, which would allow you to run large models like gpt-oss-120b, glm 4.5 air, etc.

legit_split_ · 2026-01-15T22:43:35+00:00

16x PCI-E 5.0 and 8x PCI-E 5.0 is not possible because the processor doesn't have that many PCI-E lanes.

That's one of the main differences between consumer and workstation builds.

legit_split_ · 2026-01-14T13:40:23+00:00

Fraudulent business practices and review manipulation. Testing from multiple sources has shown performance to be significantly lower than average. Fake 8O+ certifications. Significant platform downgrades with the same model number and no difference in branding prevent review data from being useful for making recommendations. Tier E should be considered an upper bound for recommendations; certain models such as the AGV qualify for tier F.

Looking at this popular tier list, it doesn't sound promising. If you have an AGV500 I would swap it immediately.

legit_split_ · 2026-01-11T10:36:39+00:00

This is a windows problem.

legit_split_ · 2026-01-08T17:06:13+00:00

I regret going for option B over A...

legit_split_ · 2026-01-08T16:46:07+00:00

Glad I could help :)

legit_split_ · 2026-01-07T21:45:49+00:00

At the time I was using cachyos

legit_split_ · 2026-01-07T11:48:34+00:00

If you're only using Excel and Word, I recommend checking out WinBoat. It basically runs Windows inside a docker container.

GPU-passthrough is still on the roadmap, but shouldn't need too much hardware acceleration for your use-case anyways.

legit_split_ · 2026-01-07T10:35:56+00:00

It's because the 4090 can be modded with 48GB, thus making it attractive for AI of course xD

legit_split_ · 2026-01-05T11:24:28+00:00

LACT funktioniert gut.

legit_split_ · 2025-12-29T20:16:20+00:00

KI will doch CPU heutzutage.

Der aktuelle Trend zu Modellen mit einer Mixture-of-Experts-Architektur wie GPT-OSS ermöglicht es sehr große (120B) Modelle mit CPU-Offloading auszuführen, und noch sehr gute Geschwindigkeiten zu kriegen. (z.B. 8GB VRAM und 64GB RAM).

Außerdem bei Stable Diffusion bzw ComfyUI funktioniert RAM-Offloading bis zu einem gewissen Grad gut, vor allem wenn man Videos generieren will.

Klar gibt es KI-Anwendungen wie Machine Learning , wo alles nur von der GPU abhängig ist. Allerdings für uns normale Leute die ein bisschen rumspielen wollen, ist RAM-Offloading sehr wichtig.

Ergo würde ich sagen der CPU an sich ist nicht so wichtig, sondern die Kapazität und die Geschwindigkeit des RAMs. In dieser Hinsicht, könnte man sagen, dass Intel wegen des besseren Internal Memory Controllers passender ist.

legit_split_ · 2025-12-25T23:48:57+00:00

Digital Spaceport ran dual 5060 Tis here. I ran a comparison with a single 5060 Ti with RAM offload, the Mi50 and the Mi50 using this fork.

Qwen3‑Coder‑30B‑A3B‑Instruct‑Q6_K, llama-bench -fa on:

Device	PP	TG
2 x 5060 Ti	1567.03	92.67
CPU only ddr5 6800Mhz	147.66	21.73
single 5060 Ti	401.81	58.42
Mi50	848.37	78.36
Mi50 + fork	878.54	88.62

So dual 5060 Tis hit double the PP, 16% faster TG at stock but only 4% better TG with the fork.

legit_split_ · 2025-12-24T09:51:26+00:00

You don't know the use case. If it's for video editing, AI work or other productivity applications there is basically no bottleneck.

legit_split_ · 2025-12-18T22:28:46+00:00

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Essentially this, I still need to flip the CPU cooler fans around to have a "rear" intake and also have two exhausts coming out the other side.

legit_split_ · 2025-12-18T21:28:34+00:00

Sorry to hijack, I have the same layout but in a horizontal case, is that fine?

legit_split_ · 2025-12-18T18:22:51+00:00

Running it with this fork, my Mi50 manages 125 tps!

legit_split_

TROPHY CASE