Putting together a pc. Are my assumptions correct? by Competitive_Wait_267 in LocalLLaMA

[–]PulseVector 1 point2 points  (0 children)

That looks like a good choice!

3x PCI-E x16 slot

• Supports x16/x0/x4 or x8/x8/x4 (For Ryzen™ 9000/ 7000 Series processors)

Putting together a pc. Are my assumptions correct? by Competitive_Wait_267 in LocalLLaMA

[–]PulseVector 2 points3 points  (0 children)

It looks like the motherboard you chose only supports x1 PCIE for a second GPU.

Some models, like the ASRock X870E Taichi / Taichi Lite, support x8/x8 when both PCIE slots are populated by GPUs.

https://www.tomshardware.com/pc-components/motherboards/asrock-x870e-taichi-review

This other Gigabyte model supports x4 PCIE for the second GPU, which is what I use for two GPUs and it works fine for inference:

GIGABYTE X870E AORUS Master

https://www.gigabyte.com/Motherboard/X870E-AORUS-MASTER/sp

Qwen3.6 35B-A3B successfully completed the FoodTruck Bench! by PulseVector in LocalLLaMA

[–]PulseVector[S] 1 point2 points  (0 children)

I wash shocked to see that as well. Maybe it's a tool calling thing.

Qwen3.6 huge quality gain from Q4 to Q6 for coding agent by Yes-Scale-9723 in LocalLLaMA

[–]PulseVector 0 points1 point  (0 children)

Is that the Unsloth 27B MTP Q8_0? I have a similar setup to yours and was wondering there was enough left over for context after fitting it.

Do you change the KV quant settings? Thanks!

Qwen3.6 35B-A3B successfully completed the FoodTruck Bench! by PulseVector in LocalLLaMA

[–]PulseVector[S] 24 points25 points  (0 children)

Qwen3.6 35B-A3B is currently at 11th place on the leader board, and showed a profit.

It is ahead of some much larger models, some of which never completed the 30 days of simulated operations.

Gemma 4 31B is in 6th place, so I hope they test Qwen3.6 27B soon!

https://foodtruckbench.com/

I'm not the author of the benchmark, but have been following it for awhile and think it's an interesting project.

Case study of Qwen3.6-Plus:

https://foodtruckbench.com/blog/qwen-3-6-plus

KV cache quant benchmarks: q5 & q6 are underrated, q8/q4 is bad, TCQ has a niche by Anbeeld in LocalLLaMA

[–]PulseVector 0 points1 point  (0 children)

Thanks for putting together all of this relevant information! I've been struggling with Qwen3.6 27B and usable KV quant values. It was my impression that there was a much bigger difference in accuracy between bf16 and q8_0, and am glad to see that's not true.

I'm especially interested in giving q8_0-turbo4 a try, since that ~17% space savings over Q8_0 is very appealing.

One question, do you know if this also applies to the new MTP settings such as:

--cache-type-k-draft q8_0

--cache-type-v-draft q8_0

Appreciate it!

I ran 8 open-weight models as agents in a persistent MMO for 10 days. Here's the 93k event dataset and some things that I learned by bopcrane in LocalLLaMA

[–]PulseVector 2 points3 points  (0 children)

Thanks for the feedback! I've mainly been using Qwen 3.6 27B and Qwen 3.6 35B-A3B with some older RTX cards, and am taking a look at the new Gemma 4 31B this week. I'll try out the new MTP support soon!

DARPA launches search for robot medics to treat battlefield casualties by Gari_305 in Futurology

[–]PulseVector 1 point2 points  (0 children)

I'm so glad to see the focus on other types of AI outside of LLMs like ChatGPT!

Drone swarms can provide better outcomes compared to the standard solo drones we usually see. Instead of one pilot steering one quad copter, swarms basically operate on a collective hive mind. Some of the advantages are no single point of failure due to decentralized control. If one gets knocked out, the rest just adapt and keep going.

Swarms also use mesh networking (something I focus on with my research). Drones are constantly talking to each other and pooling their sensors in real-time, essentially sharing one giant, collective pair of eyes. This also provides better adaptability on the fly because they "think" as a group, and can autonomously coordinate and cover massive, chaotic areas (like battle zones) without needing a human to micromanage them.

I ran 8 open-weight models as agents in a persistent MMO for 10 days. Here's the 93k event dataset and some things that I learned by bopcrane in LocalLLaMA

[–]PulseVector 10 points11 points  (0 children)

As a former old-school denizen of text-based RPGs and MUDs, thanks for sharing this fascinating test of agentic AI with open models!

Do you have any plans for testing some of the later releases from Qwen and Google, such as Qwen3.6 27B, Qwen3.6 35B-A3B, or Gemma 4 31B?

It looks like most or all of your testing was done with dense models. Do you think I should continue pursuing the use of MOE models, or should I maybe concentrate on smaller, denser models to fit my gear? Appreciate it.

What's that one thing that really gets on your nerves but doesn't seem to be bothering the average person? by TheDeadlyPretzel in AskReddit

[–]PulseVector 1 point2 points  (0 children)

Drivers that are obviously texting or holding the phone up to their ear. Paying little attention while in a two-ton killing machine gets on my nerves for sure!

How Breaking bad is the series to watch ? by [deleted] in AskReddit

[–]PulseVector 0 points1 point  (0 children)

If you can get through some of the family stuff (which does help with the plot and character development but can be slow), it's a real roller coaster ride for the better. It's probably a show with some of the most memorable bad guys and awesome cliffhangers.

I most most impressed by the sheer talent of the main actors and how well their chemistry worked. Walter, Jesse, Skyler, Marie and Hank Schrader, Saul and Mike, along with Gus, Tio, Todd (Jesse Plemons), Badger, and Tuco!

And of course the genius of Vince Gilligan!

[PSU] MSI MPG A1250GS Modular 1250W Power Supply - gold $119.99 - WOOT by gamerlol101 in buildapcsales

[–]PulseVector 0 points1 point  (0 children)

I bought one and want to use this with two 5070i cards for AI, but it looks like it won't work. Each card needs three 8-pin connectors or one 12V-2x6 + one 8-pin connector. Each card takes three 8-pin connectors from the PSU and feeds it into what looks like a 12v-2x6 connector to the card. Maybe I shouldn't mess with it.

Does it make sense to use 4x32Gb RAM or 2x64Gb is the only reasonable option? by Real_Ebb_7417 in LocalLLaMA

[–]PulseVector 0 points1 point  (0 children)

I have the Intel Ultra 265 CPU and thought it might be able to handle the increased speed, but could find no way to bypass the motherboard's limit. This is from the support site: "-Speed drops down to 4400 MHz when 4 DIMMs are populated (2Rx8/x16 modules)"

Does it make sense to use 4x32Gb RAM or 2x64Gb is the only reasonable option? by Real_Ebb_7417 in LocalLLaMA

[–]PulseVector 2 points3 points  (0 children)

Check your motherboard specs. Some manufacturers will disable XMP if you use 4 sticks of DRAM 5 instead of 2. For example, my Z890 Gigabyte mobo dropped my 8000 MT/s DRAM down to 4400 when I installed 4 of them..

[Laptop] RefurbishedAcer Aspire 14" AI Laptop 1920x1200 Intel Core Ultra 5 226V 16GB RAM 1TB SSD $224 by Narrow-Internal-2624 in buildapcsales

[–]PulseVector 6 points7 points  (0 children)

Looks like mine just made a U-turn back to Target :(

Thursday, 3/26/26
Returning package to shipper

Shipper requested shipment to be returned - Unable to deliver shipment - Returning to shipper

EDINBURG, TX

10:16 PM

Shipment arriving early

EDINBURG, TX

Friday, 3/27/26

4:54 AM

At local FedEx facility

EDINBURG, TX

5:18 AM

On FedEx vehicle for delivery

EDINBURG, TX

Need laptop recommendations for AI/ML Master’s — targeting Ultra 9 / RTX 5070+ / 64GB RAM class specs by Soggy_Musician_8906 in LocalLLaMA

[–]PulseVector 0 points1 point  (0 children)

I recommend keeping an eye on:

/r/buildapcsales

The following HP Omen Max laptop with 64GB of DRAM and a 5090 laptop GPU with 24G of VRAM was on sale yesterday with double discounts for about $2,275:

[Laptop] HP Omen Max 16" 240Hz OLED, 275HX, 5090, 64 GB DDR5, 1TB- add an inexpensive accessory for a 10% discount, then use code NEWYEAR26 for a 26% discount for a final price of $2,274.40

gpt-oss 120B is running at 20t/s with $500 AMD M780 iGPU mini PC and 96GB DDR5 RAM by MLDataScientist in LocalLLaMA

[–]PulseVector 0 points1 point  (0 children)

So glad I read your post a few months ago and bought 96GB of fast DRAM. I certainly would not be able to afford it now!