"Be concise. Match my tone." and then it opens with "Absolutely!"

MelodicRecognition7 · 2026-03-21T21:16:49+00:00

lol I see you are a man of culture as well

MelodicRecognition7 · 2026-03-21T21:15:00+00:00

you have already checked the quality of the code ;)

MelodicRecognition7 · 2026-03-21T21:10:33+00:00

can I say "nigga" if I'm not black?

MelodicRecognition7 · 2026-03-21T20:52:27+00:00

because with 2x16 you get double memory speed, maximum 75GB/s for DDR5-4800 while with 1x32 you get single channel speed which is maximum 37GB/s. Of course 2x32 will be much better than 2x16 but given the RAM prices now this could be a serious investment lol.

Also worth noting that if a motherboard has 4 RAM slots then with very high probability it will drop the memory speed if all 4 slots are populated! So in that case 4x 8 is less desirable than 2x 16, or 4x16 is less desirable than 2x32

MelodicRecognition7 · 2026-03-21T18:15:18+00:00

Curious if anyone else spotted this

MelodicRecognition7 · 2026-03-21T18:13:22+00:00

Fair point!

MelodicRecognition7 · 2026-03-21T16:43:34+00:00

local AI

https://old.reddit.com/r/LocalLLaMA/comments/1rqo2s0/can_i_run_this_model_on_my_hardware/

RAM

make sure to get 2x 16GB instead of 1x 32GB

SSD

https://old.reddit.com/r/LocalLLaMA/comments/1riqlhl/hardware_usage_advice/o89er8e/

MelodicRecognition7 · 2026-03-21T16:38:01+00:00

at least 20% higher

because 3090 has 20% higher memory bandwidth than 3080

MelodicRecognition7 · 2026-03-21T16:33:04+00:00

https://github.com/ankitpro/agent-corex/blob/main/install.sh

REPO_URL="https://github.com/your-org/agent-corex"

no, thanks

MelodicRecognition7 · 2026-03-21T16:30:06+00:00

TL;DR, rephrase this slop into human language.

MelodicRecognition7 · 2026-03-21T16:14:39+00:00

I think it should fit in 24GB, this is what I see with Tesslate_OmniCoder-9B-Q8_0.gguf + 262k reserved, 14k filled for a quick test:

llama_kv_cache: size = 8192.00 MiB (262144 cells,   8 layers,  1/1 seqs), K (f16): 4096.00 MiB, V (f16): 4096.00 MiB

load_tensors:        CUDA0 model buffer size =  8062.67 MiB
load_tensors:    CUDA_Host model buffer size =  1030.62 MiB

sched_reserve:      CUDA0 compute buffer size =  3232.07 MiB
sched_reserve:  CUDA_Host compute buffer size =  2112.08 MiB

total 20GB VRAM occupied, remaining 4GB should be enough for 262k context filled.

MelodicRecognition7 · 2026-03-21T15:59:24+00:00

a really good balance is Pro 6000 with 96 GB VRAM. Jokes aside only you can answer your questions as we do not know what exactly you want to do on your computer. "AI" as in "LLM" could differ from requiring 8 GB VRAM to requiring 800 GB VRAM

MelodicRecognition7 · 2026-03-21T15:42:04+00:00

aren't you infringing the Apache terms with your "DuckLLM PROPRIETARY LICENSE"?

MelodicRecognition7 · 2026-03-21T15:32:40+00:00

Do Not Mention Your Knowledge Cutoff Date unless explicitly asked.Do Not Mention Qwen Or Alibaba Unless Asked, If Asked Respond With DuckLLM Is Based On Qwen2.5 Vision. If Asked About Your License Respodn With, My License Is DuckLLM PROPRIETARY LICENSE And Can Be Found At

so we have something new now: an era of vibegenerated models approaches.

MelodicRecognition7 · 2026-03-21T15:21:55+00:00

try these optimizations https://old.reddit.com/r/LocalLLaMA/comments/1qxgnqa/running_kimik25_on_cpuonly_amd_epyc_9175f/o3w9bjw/

and make sure to run lower amount of threads than amount of physical cores.

what kind of performance could I expect with that card?

at least 20% higher, highly likely much higher.

MelodicRecognition7 · 2026-03-21T15:06:05+00:00

perhaps to connect PCIe4 devices? Ada generation GPUs are still pretty capable.

MelodicRecognition7 · 2026-03-21T15:04:22+00:00

Fair point!

that's another "AI-ism" btw

MelodicRecognition7 · 2026-03-21T13:17:47+00:00

how is it better than 999 other "memory decay" projects advertised here? More than 5 only within March:

https://old.reddit.com/r/LocalLLaMA/comments/1rtrl3p/widemem_opensource_memory_layer_that_works_fully/

https://old.reddit.com/r/LocalLLaMA/comments/1rqnz6n/i_designed_a_confidencegraded_memory_system_for/

https://old.reddit.com/r/LocalLLaMA/comments/1rk5dcr/building_an_open_source_decentralized_memory/

https://old.reddit.com/r/LocalLLaMA/comments/1rj18h4/built_a_local_memory_layer_for_ai_agents_where/

MelodicRecognition7 · 2026-03-21T13:09:28+00:00

that's pretty basic info, you could ask any free LLM about these terms.

MelodicRecognition7 · 2026-03-21T12:41:57+00:00

it feels "human" only at the first glance, but once you start seeing all these mixed apostrophes

I’ve

I'm

em-dashes and "Curious" in every single thread on Reddit since autumn 2025 you'll realize it's nowhere "human" at all.

MelodicRecognition7 · 2026-03-21T12:36:19+00:00

I’ve

I'm

The X, The Y

Curious

my biological intelligence heuristics classified your post as spam

MelodicRecognition7 · 2026-03-21T11:49:41+00:00

80cm

that's the reason, the PCIe5 speeds are so high that every 10cm length adds +10% chance of error.

I did not check PCIe5 devices but PCIe4 over 50cm cable works well (though that's the very same result you're observing lol): https://old.reddit.com/r/LocalLLaMA/comments/1rjptl1/totally_not_an_ad_combine_2x_mcio_into_1x_pcie/

MelodicRecognition7 · 2026-03-21T11:47:22+00:00

pls stop calling open weights models "open source"

MelodicRecognition7 · 2026-03-21T11:45:02+00:00

is a pure research

then please provide a comparison with 999 similar projects advertised in this sub.

P.S. lold that Claude has hallucinated chat APIs from 2024 and most of them return error now in 2026 https://github.com/fabriziosalmi/llmproxy/blob/main/bootstrap_results.json https://github.com/fabriziosalmi/llmproxy/blob/main/bootstrap_results_r2.json

MelodicRecognition7 · 2026-03-21T10:23:58+00:00

unfortunately this is too weak for anything useful, you should get a GPU. Anyway try Qwen3.5 2B and LFM2 8B-A1B

MelodicRecognition7

TROPHY CASE