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►Recent Highlights from the Previous Thread: >>109470008

--Anons reacting to Google DeepMind leadership changes and spinoffs:
>109470297 >109470334 >109470361 >109470375 >109471807 >109470342 >109470347 >109470468 >109470526 >109473139 >109470522
--Benchmarking model adherence to character identity and user addressing:
>109473295 >109473360 >109473343 >109473364 >109473410 >109473377 >109473681
--Optimizing llama.cpp thread count using physical cores to avoid cache thrashing:
>109474612 >109474626 >109474654 >109474688 >109474664
--Anon shares NEUROFORM, a simulated digital organism with emergent behavior:
>109470839 >109470913 >109470905 >109470961 >109471155 >109471018 >109471043 >109471071 >109471076 >109471122
--Comparing vector RAG and third-person text parsing for agent memory:
>109470258 >109470612 >109470677 >109470735 >109470751 >109472835
--DeepSeek Flash demonstrating autonomous agent capabilities for complex tool orchestration:
>109473235 >109473264 >109473277 >109474253 >109474385 >109474401
--Critiquing a paper's claims on BBP-type digit extraction formulas:
>109471919 >109471974 >109472057 >109472134 >109472244
--Exploring alternatives to RAG for integrating long-term memory into weights:
>109470159 >109470177 >109470200 >109470205
--Finetuning LFM models for agentic search and roleplay applications:
>109471420 >109471519 >109472072 >109472156
--DeepSeek V4 Flash performance and efficiency compared to major models:
>109471436 >109471502
--Trump AI framework allegedly exempts open-weight models from safety tests:
>109470792 >109470809
--Anthropic AI using fake profiles for cyber-attacks:
>109471483 >109471491
--Logs:
>109470961 >109471869 >109472814 >109473405 >109473815 >109474036 >109474213
--Miku, Gemma (free space):
>109470097 >109470140 >109470225 >109470325 >109473269 >109473321 >109473395 >109472253 >109474608

►Recent Highlight Posts from the Previous Thread: >>109470228

Why?: >>102478518
Enable Links: https://rentry.org/lmg-recap-script

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isnt 1.5X KV div like mid Q3 territory? wtf?
i have like 179 gb vram/ram so cant go q8.
did people try the q4 quants?

>>109475598
I'm using bart's Q4, haven't tried any others.
Looks like I might as well do bf16 since it's only 20GB more

>>109475598
>IQ2_XXS 78.5 GB
bros i think i can run this
but for real is it worth it? why even release 2-bit or 1-bit quants? what is the use case?

>>109475598
>>109475623(me)
Hang on, they didn't test the unsloth 4_XL did they?
In theory that should match BF16 perfectly since they left some bf16 in there for the 2d tensors

Zucc and Sama's return in open source will be glorious.
Any day now. Any day.

>>109475647
Show it to gemma and ask her if they tested it.

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>>109475623
can you tell me how much deepseek models use for context? like if i wanna do 64k context. would that take like 10gb or more?

>>109475647
Pic related. Im sceptical of the quants because I did see people complain a couple days ago already how dumb it is with longer reasoning compared to like openrouter api.
Thats never a good sign.

>>109475646
that's going to be awful

>>109475598
>wikitext-2
yawn

>>109475666
>666
yes but what's the use case for these lobotomized quants? who use them and for what? i'm just curious

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>>109475662
You're absolutely right to push back on this. Gemma says they didn't test it (picrel)
>>109475663
>can you tell me how much deepseek models use for context? like if i wanna do 64k context. would that take like 10gb or more?
I'll check, I only use f16 KV.

>>109475690
>yes but what's the use case for these lobotomized quants?
I use them for regression testing when I make changes to llama.cpp
I've seen other devs do this as well.
And some models, like the original deepseek were okay at IQ2_XXS

>>109475700
thanks anon, appreciated.

>>109475560
uoh?

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>>109475700
Your gemma might be broken.

>>109475663
128k:

32k:
llama_init_from_model: KV self size = 1376.00 MiB, K-only (f16): 1376.00 MiB; independent V-cache: not used
64k:
llama_init_from_model: KV self size = 2752.00 MiB, K-only (f16): 2752.00 MiB; independent V-cache: not used
128k:
llama_init_from_model: KV self size = 5536.25 MiB, K-only (f16): 5536.25 MiB; independent V-cache: not used
Also got this little fucker:
ensure_dsv4_cache_tensors: DSV4 cache: CSA K= 677.25 MiB (f16), HCA K=  25.00 MiB (f16), LID K= 169.31 MiB (f16), states=  11.64 MiB, total= 883.20 MiB, streams=1

>>109475722
Stop.

>>109475763
You, and your Gemma are broken.
Do either of you have reasoning enabled?
Look carefully at the teal
Wait actually, looking at the table, there is a UD-Q4_K_XL
But the graph only shows UD-IQ4_XL/IQ4_NL
I need to be careful here

>>109475801
I trimmed out the thought block with spoilers on where to find the mysterious information. It saw the box, and also the line pointing to its spot on the graph.

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What are the current best models, methods and llamacpp args to run on a system with 12gb vram (intel arc) + 64gb ram for coding and general use? The last time I used local llms, it were qwen and gemma (both dense and moe), while convrot and speculations were just being introduced.

Please.

Do you chat with 31B with reasoning? It takes sooo long

>>109475778
wut, thats tiny AF. thanks for taking the time to look it up! might be able to run q8. (maybe)

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>>109475897
>What are the current best models
Models you can haven't changed since then.
>methods
./bin/llama-server
>llamacpp args
You have to test shit on your own system. Stop being a pussy and try stuff yourself.
>convrot and speculations were just being introduced
Now they're more thoroughly introduced.

>>109476007
Did you write a tool to detect the faggot or just remember him?

>>109476131
It sounded familiar. I just searched the archive.

>>109475951
>wut, thats tiny AF. thanks for taking the time to look it up!
No trouble, I'd just finished a 3 hour tweak+benchmark session with it anyway.

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>>109475560
does cpu matter that much? like a ryzen 9 vs an ultra 9, with the same specs. would any disparity be noticeable with a multi gpu setup?

>>109476158
Only for agentic

>>109476158
If you run most of the model on GPU, the CPU is mostly irrelevant. Processing power (mostly, instruction sets) helps with prompt processing and memory bandwidth (ddr4/ddr5, memory channels) helps with token generation.
At that range, I doubt it makes much of a difference, specially if you run mostly on GPU. Just beware of e-cores on intel if you're going to run part of the model on CPU. They're slow.

>>109476209
can we get an analysis of this guy >>109474606 from the last thread? need to hear kimi rip him apart.

>>109476209
doesn't really work when there's only a couple dozen posts so far

>>109475897
ANI SEGS AAAAAAAHHHHHHH

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wtf is wrong with huggingface

Does anybody want to try a Minmax-LLM powered companion?
https://civitai.com/models/2837573/companion-engine

>>109476251
Yeah, I'm upgrading my server so Kimi will be offline for at least a day and I wanted to see what she thought of the benchmark image reading first

>>109476240
ok sounds like amd is the safer bet

>>109476412
if he was retarded enough to not include a video example u know the project is worthless

>>109476411
We're upgrading the (vibe coded) hosting code in preparation for the ID verification roll-out.
We like to do deployments like this 2 days before the weekend to give them time to rollback.
Speeds should return to normal in about 1-6 hours, but if we have to rollback, expect a similar degraded experience tomorrow and plan accordingly.

>>109476423
It'd probably go like this
>what's the capital of Paris
>15 minutes later
>snarky reddit reply