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or990to | LocalLLaMA | 1u30vzx | 1u30vzx | 0 | FullOf_Bad_Ideas | 1,781,281,543 | I have 96GB of RAM and 192 GB of VRAM. I don't use that RAM, but some things were crashing when I had 32GB in there.
My personal preference is to VRAMmaxx, especially with how expensive DDR5 is.
I think this build is like 35k euro or so, right?
I'd cheap out on CPU, cheap out on RAM and stack as much RTX 6000 Pro no... | 1 | null | /r/LocalLLaMA/comments/1u30vzx/all_in_vram_or_balance/or990to/ | 1,789,194,932 | batch-priority-2026-summer |
ora5qr9 | LocalLLaMA | 1u30vzx | or990to | 1 | zakadit | 1,781,290,378 | you'r full of great ideas!
*edit: wait...* | 2 | null | /r/LocalLLaMA/comments/1u30vzx/all_in_vram_or_balance/ora5qr9/ | 1,789,194,938 | batch-priority-2026-summer |
ora7yvx | LocalLLaMA | 1u30vzx | ora5qr9 | 2 | FullOf_Bad_Ideas | 1,781,290,990 | There was a time when having a lot of RAM made sense, but the recent prices hit RAM more than VRAM and I think building a new system for running hybrid inference is just not cost-effective given what you'll be able to actually run. There is one guy running Kimi on I think 512GB of RAM and 4x 3090 (Lissanro), and that's... | 1 | null | /r/LocalLLaMA/comments/1u30vzx/all_in_vram_or_balance/ora7yvx/ | 1,789,194,938 | batch-priority-2026-summer |
orab3cb | LocalLLaMA | 1u30vzx | ora7yvx | 3 | zakadit | 1,781,291,863 | Of course, and to be honest I'll probably apply them (with a bit of research first).
It's kind of obscure to me, frankly, figuring out how much is *enough*. I'll admit I'm still somewhat of a newbie even though I've been digging into it pretty hard.
If you could explain it, or point me to a solid post (or anything el... | 1 | null | /r/LocalLLaMA/comments/1u30vzx/all_in_vram_or_balance/orab3cb/ | 1,789,194,938 | batch-priority-2026-summer |
orakh2q | LocalLLaMA | 1u30vzx | orab3cb | 4 | FullOf_Bad_Ideas | 1,781,294,500 | > It's kind of obscure to me, frankly, figuring out how much is enough. I'll admit I'm still somewhat of a newbie even though I've been digging into it pretty hard.
There's never enough if a new open weight model is 1T/1.6T, you would like to try it and you can't run it.
I'd recommend spending $100 on renting various... | 1 | null | /r/LocalLLaMA/comments/1u30vzx/all_in_vram_or_balance/orakh2q/ | 1,789,194,938 | batch-priority-2026-summer |
osbgd12 | LocalLLaMA | 1u30vzx | orakh2q | 5 | zakadit | 1,781,755,493 | Glm-5.2 has destroyed my aim for a budget, also im on a business trip (doing shenzen, hongkong, jakarta and singapor)
Do you think it's "safe" to buy something there (singapor seems obviously ok but for the other idk, they're pretty attracting with those (not so) fancy prices)
Also, idk why i didn't put a eye on i... | 1 | null | /r/LocalLLaMA/comments/1u30vzx/all_in_vram_or_balance/osbgd12/ | 1,789,194,938 | batch-priority-2026-summer |
osc7t5w | LocalLLaMA | 1u30vzx | osbgd12 | 6 | FullOf_Bad_Ideas | 1,781,768,418 | No idea about hardware from those places and how how safe it is. As far as I know, pricing on online places like Alibaba is pretty close to what you get when your are in person, while you have better overview of all options and their prices by browsing online.
>Also, idk why i didn't put a eye on it before but is DGX ... | 1 | null | /r/LocalLLaMA/comments/1u30vzx/all_in_vram_or_balance/osc7t5w/ | 1,789,194,938 | batch-priority-2026-summer |
or1ph1y | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | giveen | 1,781,190,136 | \### The TL;DR Use the Q4\_K\_M quantization. It’s not just smaller; it hits significantly higher token speeds (+44%) and allows for 50% more context than Q6\_K on this hardware.
\### The Magic Numbers I found that t-max and t-min are your primary levers for speed. Lowering them reduces the denoising steps required fo... | -3 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1qctq | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | cleversmoke | 1,781,190,379 | 250 tok/s is wild. Would love to see 90k+ context. How's the quality of the output you're seeing at the context levels you're testing on? | 4 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1qspz | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | 1,781,190,502 | 9 | null | null | 1,789,194,932 | batch-priority-2026-summer | ||
or1rf19 | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | nsfnd | 1,781,190,672 | vllm, nvidia/diffusiongemma-26B-A4B-it-NVFP4.
I get;
GPU KV cache size: 945,291 tokens
Maximum concurrency for 262,144 tokens per request: 3.61x
~500 tok/s. (400watt limited)
But fails miserably on pi and opencode.
Using claude code produced some results, but no where near qwen3.6 27b. | 28 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1w1gl | LocalLLaMA | 1u31hk8 | or1rf19 | 1 | Luke2642 | 1,781,191,910 | Exactly. Even the Google blog has it as 5% lower intelligence than Gemma4 12B. It looks good for fine tuning on specific tasks though. | 15 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1wo8n | LocalLLaMA | 1u31hk8 | or1qctq | 1 | giveen | 1,781,192,078 | I havent been able to push context very high, its been miserable, maybe I'm just not understanding the technology enough. | 5 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1wp9g | LocalLLaMA | 1u31hk8 | or1w1gl | 2 | nsfnd | 1,781,192,086 | more than that, i think streaming should be disabled, so the whole response arrives as one piece at the end.
i checked and none of the coding agents i listed above supports that.
| 6 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1x2x8 | LocalLLaMA | 1u31hk8 | or1rf19 | 1 | giveen | 1,781,192,187 | My workflow theory for coding ideas would be Diffusion (initial scaffolding and idea generation) -> Deepseek flash (most coding done here, complete codebase aware) -> Deepseek Pro (debug and cleanup) | 5 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1xb6q | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | pmttyji | 1,781,192,249 | Could you please format(Use Codeblock for config & output) your thread? Thanks | 8 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1xrc6 | LocalLLaMA | 1u31hk8 | or1xb6q | 1 | giveen | 1,781,192,369 | Sure, let me try 😄 | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1y4vs | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | Adventurous-Paper566 | 1,781,192,469 | Meh | 9 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1zhq0 | LocalLLaMA | 1u31hk8 | or1y4vs | 1 | mister2d | 1,781,192,829 | Yeah it looks like a lot of noise that I have to denoise myself. | 16 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1zoch | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | MapSensitive9894 | 1,781,192,878 | Thanks for testing, I’m getting tired of rebuilding llama pr’s. interesting to see how the diffusion model affects speed and tasks | 2 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or20o3q | LocalLLaMA | 1u31hk8 | or1zhq0 | 2 | giveen | 1,781,193,141 | I could see how this might help frontier models but faster crappy output isnt what i'm looking for either.
250tks = crap I am going to have to go bck over and over and over
20 tk/s = at least its working
10tk/s = I can wait as long as its right. | 9 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or211il | LocalLLaMA | 1u31hk8 | or1zoch | 1 | giveen | 1,781,193,239 | I trust the llama.cpp team far better than my simple tests. They have to think big picture and how one PR could impact others and cause other issues.
I just think its fun to test out some frontier ideas. | 2 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or21s5t | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | Klutzy-Snow8016 | 1,781,193,433 | >\*\*Temperature is everything\*\* — lowering t-max from 0.8→0.3 and t-min from 0.4→0.05 accounts for virtually all the speedup. The rest of the EB params are already well-tuned at defaults.
Have you compared the quality of the output with these settings vs the defaults? I think these changes should give worse results... | 3 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or23a4a | LocalLLaMA | 1u31hk8 | or21s5t | 1 | giveen | 1,781,193,832 | I'm running a secondary benchmark right now, and fact checking its responses to see quality of output vs speed. | 2 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or25peh | LocalLLaMA | 1u31hk8 | or21s5t | 1 | giveen | 1,781,194,477 | Prompt:
Explain quantum entanglement in simple terms. Include at least one analogy and explain why Einstein called it "spooky action at a distance.
Both outputs share the same physics oversimplifications — these are \*\*knowledge boundary issues in the model\*\*, not tuning artifacts. The model confidently makes th... | 3 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or27so7 | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | Healthy-Nebula-3603 | 1,781,195,031 | As most people suspected diffusion models suck ...
So models quality:
Dense > MOE >> diffusion | 7 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or280il | LocalLLaMA | 1u31hk8 | or1qctq | 1 | Healthy-Nebula-3603 | 1,781,195,088 | You can't get such big context on diffusion model with 32 GB vram | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or29s28 | LocalLLaMA | 1u31hk8 | or1x2x8 | 2 | jesuschrist-69420 | 1,781,195,554 | Diffusion model does draft like mtp | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or29vjq | LocalLLaMA | 1u31hk8 | or1w1gl | 2 | Noob_Krusher3000 | 1,781,195,580 | Would it be possible to use this for speculative decoding? | 6 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or2kk16 | LocalLLaMA | 1u31hk8 | or1x2x8 | 2 | Ok_Technology_5962 | 1,781,198,409 | The issue for smaller model as idea go code generator is the poor ideas that the larger one has to fix by rewriting the whole thing. But first pass implementation based on a detailed guide the large model puts together including requirments might work | 4 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or2qd4r | LocalLLaMA | 1u31hk8 | or1rf19 | 1 | sixx7 | 1,781,199,921 | > But fails miserably on pi and opencode.
No tool-calling support (yet). Won't really work in any harness | 6 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or2ygba | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | 10F1 | 1,781,202,034 | It still can't run with llama-server, right? | 2 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or30xq2 | LocalLLaMA | 1u31hk8 | or1rf19 | 1 | MerePotato | 1,781,202,690 | This seems more like a general assistant or bulk data processing kinda model than a coding agent | 3 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or310v7 | LocalLLaMA | 1u31hk8 | or1qspz | 1 | MerePotato | 1,781,202,712 | Lemme guess, you're quanting KV | 4 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or37hk9 | LocalLLaMA | 1u31hk8 | or310v7 | 2 | 1,781,204,428 | 4 | null | null | 1,789,194,932 | batch-priority-2026-summer | ||
or380r0 | LocalLLaMA | 1u31hk8 | or2ygba | 1 | giveen | 1,781,204,571 | nope cli only | 2 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or386un | LocalLLaMA | 1u31hk8 | or2kk16 | 3 | giveen | 1,781,204,617 | Hm, never thought about it that way, maybe i'm working in the wrong order? | 2 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or38lbe | LocalLLaMA | 1u31hk8 | or29s28 | 3 | Ok_Technology_5962 | 1,781,204,725 | Would be great for a 124b model dont you think? | 2 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or3kxya | LocalLLaMA | 1u31hk8 | or27so7 | 1 | z_latent | 1,781,208,045 | Well, speculative diffusion like DFlash doesn't suck, so I'd say there's potential in the technology. | 5 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or3t6jx | LocalLLaMA | 1u31hk8 | or1wp9g | 3 | lmpdev | 1,781,210,261 | In my testing with vllm, it's still streaming, probably in 256 token chunks. And if you don't want to support streaming, it's very easy to implement it, just pretend to stream, but don't actually send anything until you have everything ready... | 4 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or405sr | LocalLLaMA | 1u31hk8 | or37hk9 | 3 | MerePotato | 1,781,212,158 | Knew it, every time someone complains about Gemma underperforming its this same mistake | 4 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or431x9 | LocalLLaMA | 1u31hk8 | or405sr | 4 | 1,781,212,977 | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer | ||
or45llx | LocalLLaMA | 1u31hk8 | or3kxya | 2 | Healthy-Nebula-3603 | 1,781,213,712 | That small model just predicting literally only the next token so works well in this scenario literally improving performance around 50-70%
Maybe the future is a hybrid model similar to MTP. | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or4hful | LocalLLaMA | 1u31hk8 | or45llx | 3 | z_latent | 1,781,217,392 | DFlash does not predict a block as large as DiffusionGemma, but it still generates a block of several (16) tokens in a single denoising step. It *is* effectively like MTP.
Also, for MoEs like Gemma 4 26B A4B the speed-up is moderate as you said (though for different reasons than you said). However, for dense models on... | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or4jfug | LocalLLaMA | 1u31hk8 | or1x2x8 | 2 | o0genesis0o | 1,781,218,044 | IMHO, it should be the other way around. The big model makes very detailed plan and goes through everything (which code module to change, in which way, not just general direction). And then small utility model with good enough tool call capability would jump in and write the code and maybe trigger tests. Then, the smal... | 3 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or4l9gx | LocalLLaMA | 1u31hk8 | or431x9 | 5 | MerePotato | 1,781,218,650 | Yes, because different architectures have different sensitivity to quantization | 2 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or4pi7b | LocalLLaMA | 1u31hk8 | or4hful | 4 | Healthy-Nebula-3603 | 1,781,220,079 | Qwen 27b MTP even for a code generation gives around 50% in crease from my experience | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or4xyod | LocalLLaMA | 1u31hk8 | or27so7 | 1 | tautality | 1,781,223,024 | Nobody is suspecting that about diffusion models, people actually suspect the opposite. Also dense / MoE is a different category than stable diffusion / not. This model is both diffusion and MoE. It's wrong to make assumptions like this from just a single example. | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or63k5p | LocalLLaMA | 1u31hk8 | or386un | 4 | Invader-Faye | 1,781,238,533 | Have the bigger model do the planning and initial scaffolding, the small /faster/dumber model finish the rest, then big model to debug for cleanup has worked very well for me. Most token burn is in that middle phase anyways | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or6y4ib | LocalLLaMA | 1u31hk8 | or1rf19 | 1 | Mart-McUH | 1,781,253,641 | Qwen 27B is dense model. To be fair compare it with MoE 35B. | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or7ulgn | LocalLLaMA | 1u31hk8 | 1u31hk8 | 0 | Plus_Confidence_1113 | 1,781,267,689 | Now compare it to the regular model with MTP.
When I experimented with it on dual 4090s I got 73 tok/s with Q8_0.
The regular model (also Q8_0 quant to be fair) produced over 240 tok/s.
Google claims 4x the throughput which it does achieve, the raw output was 1189 tok/s, but when you consider it does on average 1... | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
orbzokk | LocalLLaMA | 1u31hk8 | or2qd4r | 2 | Hufflegguf | 1,781,310,999 | The Nvidia NVFP4 quant supports tool calling (nvidia/diffusiongemma-26B-A4B-it-NVFP4). The NVFP4 RedHatAI quant seems completely jacked up to me. Running on pro6K. | 2 | null | null | 1,789,194,932 | batch-priority-2026-summer |
orcsbpy | LocalLLaMA | 1u31hk8 | orbzokk | 3 | sixx7 | 1,781,321,587 | goated, thanks | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
ory5buv | LocalLLaMA | 1u31hk8 | or29s28 | 3 | colblair | 1,781,599,106 | I switched to [sentx.ai](http://sentx.ai) for this kind of thing and it handles the draft consistency way better than diffusion. | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1rk6v | LocalLLaMA | 1u31rlg | 1u31rlg | 0 | ComplexType568 | 1,781,190,710 | I think they'd release 31B first because it needs it more... | 30 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1rzmz | LocalLLaMA | 1u31rlg | 1u31rlg | 0 | stopaskingforloginn | 1,781,190,826 | 31b is most likely next since that's the most popular model, not to mention 12b just released. | 21 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1u5jl | LocalLLaMA | 1u31rlg | 1u31rlg | 0 | ML-Future | 1,781,191,406 | I would love a DiffusionGema 4 2b with vision; I imagine many scripts whit a really fast image processor. | 13 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1unem | LocalLLaMA | 1u31rlg | 1u31rlg | 0 | jacek2023 | 1,781,191,539 | It's a MoE, are you sure there is a problem? | 0 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or22d7o | LocalLLaMA | 1u31rlg | 1u31rlg | 0 | Aaaaaaaaaeeeee | 1,781,193,587 | If the speedup between diffusion dflash and mtp was similar enough, do you need it? Since you can have QAT with QAT MTP + QAT LLM, maybe that's more valuable.
The speed also comes alongside 4B active parameters, which are already a speedup by itself! | 3 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or3828n | LocalLLaMA | 1u31rlg | 1u31rlg | 0 | ocean_protocol | 1,781,204,582 | memory's the real wall on small cards. AR streams one token so kv cache scales linearly. diffusion holds the full sequence in activation memory through every denoising step. on your 6600XT a 12B diffusion at q4 probably caps you around 1-2k tokens of context, which limits the use case but isn't fatal for short-output l... | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or3ijab | LocalLLaMA | 1u31rlg | 1u31rlg | 0 | Lucario6607 | 1,781,207,406 | Nvidia has a 14b somewhat of a diffusion model. Also 8b and 3b https://huggingface.co/collections/nvidia/nemotron-labs-diffusion | 7 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or3z6v3 | LocalLLaMA | 1u31rlg | 1u31rlg | 0 | VoiceApprehensive893 | 1,781,211,888 | i doubt 12b is a good model to do a conversion to, is it just going to be e4b but triple ram usage for more knowledge? | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or496fe | LocalLLaMA | 1u31rlg | 1u31rlg | 0 | 1,781,214,783 | 0 | null | null | 1,789,194,932 | batch-priority-2026-summer | ||
or4h7hd | LocalLLaMA | 1u31rlg | or496fe | 1 | Mrinohk | 1,781,217,316 | You sound like Claude lmao. Appeal is real, matters a lot, latency win, etc.
But yeah I was playing with it on my PC. 56 tokens a second, so about double standard gemma4 26b, but it has to generate it 29 times before it decides it's finished. Far slower. I'm sure it would be faster on the 12b since all the parameters ... | 4 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or4pp8p | LocalLLaMA | 1u31rlg | or4h7hd | 2 | fragilesleep | 1,781,220,146 | Yeah, you can see in his history that he's just been generating comments with Claude.
Compare them with his older comments:
> Yeahhh athenaa bingo , i meant this kind of characters r what kratos used to fight
> Did u used design.md ?? Pre build ui structure? | 3 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or5ej6l | LocalLLaMA | 1u31rlg | 1u31rlg | 0 | MerePotato | 1,781,228,946 | I'd much rather 31B first (as an aside, I wonder if QAT can be applied effectively to these diffusion variants) | 1 | null | null | 1,789,194,932 | batch-priority-2026-summer |
or1wt56 | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | DrBearJ3w | 1,781,192,114 | Great! | 0 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or1wt56/ | 1,789,194,933 | batch-priority-2026-summer |
or24e7k | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | no_no_no_oh_yes | 1,781,194,129 | Ill try on my 4x R9700 and report back | -1 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or24e7k/ | 1,789,194,933 | batch-priority-2026-summer |
or25tlz | LocalLLaMA | 1u31zmk | or24e7k | 1 | djdeniro | 1,781,194,508 | I don't think you should even waste your time on this, DeepSeek ran this model autonomously and compiling Cuda Graph takes about 28 minutes for each try. With eager mode it will takes around 4 minutes for launch.
Also you can download FP8 version to use it with 2x R9700 | 1 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or25tlz/ | 1,789,194,933 | batch-priority-2026-summer |
or269ro | LocalLLaMA | 1u31zmk | or24e7k | 1 | djdeniro | 1,781,194,626 | it make sense if we will got 800 tps, not 100-120.
in real case, pp will make huge latency as a result high tps on output will reduced with low speed input | 1 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or269ro/ | 1,789,194,933 | batch-priority-2026-summer |
or272r3 | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | no_no_no_oh_yes | 1,781,194,838 | I was thinking the FP8 version. But if the speed is not there (or much more), then ill keep it parked. | 1 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or272r3/ | 1,789,195,000 | batch-priority-2026-summer |
or28znr | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | Noob_Krusher3000 | 1,781,195,345 | Bro, I just heard about Diffusion Gemma and my dumbass was so excited for image generation in a local LLM. Turns out it's something different. Still exciting! I'll have to test it out anyway! | 2 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or28znr/ | 1,789,194,933 | batch-priority-2026-summer |
or29tma | LocalLLaMA | 1u31zmk | or28znr | 1 | djdeniro | 1,781,195,565 | you can generate images via ComfyUI, if you want vllm just use guide from this https://recipes.vllm.ai/Qwen/Qwen-Image | 2 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or29tma/ | 1,789,194,933 | batch-priority-2026-summer |
or2aee0 | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | Noob_Krusher3000 | 1,781,195,721 | Oh, I'm a ComfyUI enjoyer already. It's just, there are only 2 open weight autoregressive image models I can think of, they aren't particularly usable, and nobody uses them anyway. Boy, oh boy, if there was an open weight alternative to nano banana and gpt image, not just image quality, but in the LLM awareness and com... | 2 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or2aee0/ | 1,789,194,977 | batch-priority-2026-summer |
or2kcaq | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | coder543 | 1,781,198,353 | This is what I measured on DGX Spark. A nice improvement, but I wonder if there is room for more optimization. The llama.cpp config included MTP. | 9 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or2kcaq/ | 1,789,194,933 | batch-priority-2026-summer |
or2lfnp | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | annodomini | 1,781,198,642 | Have you checked out Ideogram 4? | 2 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or2lfnp/ | 1,789,195,007 | batch-priority-2026-summer |
or2mdz3 | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | mossler | 1,781,198,892 | Is your vllm-dgemma published anywhere ? | 1 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or2mdz3/ | 1,789,194,984 | batch-priority-2026-summer |
or2n9x1 | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | oxygen_addiction | 1,781,199,123 | The main bottleneck on DGX Spark is going to be memory bandwidth. | -4 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or2n9x1/ | 1,789,194,959 | batch-priority-2026-summer |
or2q6p4 | LocalLLaMA | 1u31zmk | or2n9x1 | 1 | coder543 | 1,781,199,874 | Diffusion models are compute limited, not bandwidth limited. That's the whole point. | 11 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or2q6p4/ | 1,789,194,933 | batch-priority-2026-summer |
or2qwy9 | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | z_latent | 1,781,200,064 | Shouldn't you be comparing vLLM vs vLLM? For instance, my intuition tells me DiffusionGemma should have higher TTFT than regular Gemma 4 26B A4B as it needs to generate a whole block first, which involves several forward passes. | 1 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or2qwy9/ | 1,789,194,949 | batch-priority-2026-summer |
or2rga0 | LocalLLaMA | 1u31zmk | 1u31zmk | 0 | MuzafferMahi | 1,781,200,203 | I'm testing on my 16x5090's as well!! | 3 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or2rga0/ | 1,789,194,933 | batch-priority-2026-summer |
or2u9bw | LocalLLaMA | 1u31zmk | or2lfnp | 1 | Noob_Krusher3000 | 1,781,200,932 | Yes, I have. I think using the LLM prompt template with a decently smart model is the closest we have to nano banana. Ideogram 4.0 is pretty cool. | 2 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or2u9bw/ | 1,789,194,966 | batch-priority-2026-summer |
or2uu2h | LocalLLaMA | 1u31zmk | or2qwy9 | 1 | [deleted] | 1,781,201,084 | [deleted] | 0 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or2uu2h/ | 1,789,194,933 | batch-priority-2026-summer |
or3h375 | LocalLLaMA | 1u31zmk | or2uu2h | 2 | z_latent | 1,781,207,019 | Well, as a result to share with other people, it would be a more direct comparison. But I can see your side! I too prefer llama.cpp as well and I'm looking forward to the PR, hopefully it's at least close to the vLLM numbers. | 1 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or3h375/ | 1,789,194,941 | batch-priority-2026-summer |
or4erbt | LocalLLaMA | 1u31zmk | or2mdz3 | 1 | djdeniro | 1,781,216,521 | no | 1 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or4erbt/ | 1,789,194,933 | batch-priority-2026-summer |
or53wxf | LocalLLaMA | 1u31zmk | or272r3 | 1 | jdchmiel | 1,781,225,140 | looking forward to results. | 1 | null | /r/LocalLLaMA/comments/1u31zmk/comment/or53wxf/ | 1,789,194,993 | batch-priority-2026-summer |
or1uymt | LocalLLaMA | 1u328bi | 1u328bi | 0 | AutoModerator | 1,781,191,622 | Hello! Your post was removed as you do not have sufficient karma on r/LocalLLaMa. We are doing this in response to the large volume of spam we are unfortunately experiencing. Please participate in the sub (through comments), gain the minimum of 5 karma and then re-post
*I am a bot, and this action was performed automa... | 1 | false | https://www.reddit.com/r/LocalLLaMA/comments/1u328bi/i_built_a_local_failclosed_boundary_for_ai_agent/or1uymt/ | 1,789,194,931 | batch-priority-2026-summer |
or2ekex | LocalLLaMA | 1u34lm2 | 1u34lm2 | 0 | AutoModerator | 1,781,196,829 | Hello! Your post was removed as you do not have sufficient karma on r/LocalLLaMa. We are doing this in response to the large volume of spam we are unfortunately experiencing. Please participate in the sub (through comments), gain the minimum of 5 karma and then re-post
*I am a bot, and this action was performed automa... | 1 | null | /r/LocalLLaMA/comments/1u34lm2/i_built_a_deterministic_cpuonly_gate_that/or2ekex/ | 1,789,195,772 | batch-priority-2026-summer |
or3imve | LocalLLaMA | 1u350hp | 1u350hp | 0 | floconildo | 1,781,207,433 | Nice project. I think it overlaps a bit with [Umio-Yasuno/amdgpu\_top](https://github.com/Umio-Yasuno/amdgpu_top) though, but could serve as inspiration for other features. | 3 | null | /r/LocalLLaMA/comments/1u350hp/xdnatop_unified_npuigpu_terminal_monitor_for/or3imve/ | 1,789,195,772 | batch-priority-2026-summer |
or4qnus | LocalLLaMA | 1u350hp | or3imve | 1 | westsunset | 1,781,220,470 | wow that's a great tool! feedback like this has been very helpful, thank you. There is definitely some NPU data there I wasn't collecting but would be helpful. Looking at both it look like my tool provides "Did this Ryzen AI workload actually exercise the NPU, which process owned it, and what was the iGPU doing concu... | 2 | null | /r/LocalLLaMA/comments/1u350hp/xdnatop_unified_npuigpu_terminal_monitor_for/or4qnus/ | 1,789,195,772 | batch-priority-2026-summer |
or2iyb5 | LocalLLaMA | 1u351b7 | 1u351b7 | 0 | No_Lingonberry1201 | 1,781,197,987 | I'm waiting for the opinions from when the honeymoon period wears off. GPT-4o was touted as being as capable as a PhD. | 9 | null | null | 1,789,195,773 | batch-priority-2026-summer |
or2kdfz | LocalLLaMA | 1u351b7 | 1u351b7 | 0 | LebiaseD | 1,781,198,361 | I feel like with the same harness and tool training that fable was with Claude code and Claude desktop app any other model could do the same. | 4 | null | null | 1,789,195,773 | batch-priority-2026-summer |
or2ov1m | LocalLLaMA | 1u351b7 | or2iyb5 | 1 | -dysangel- | 1,781,199,532 | based on the PhD's I've met, I think that it was undersold | 5 | null | null | 1,789,195,773 | batch-priority-2026-summer |
or2p8wm | LocalLLaMA | 1u351b7 | or2ov1m | 2 | No_Lingonberry1201 | 1,781,199,632 | Point. I worked as student IT support for a university, I know about 40% of them can tie their shoelaces without falling over. I guess they meant "as capable as a PhD should be, according to their PR." | 2 | null | null | 1,789,195,773 | batch-priority-2026-summer |
or2pha1 | LocalLLaMA | 1u351b7 | or2kdfz | 1 | dionysio211 | 1,781,199,691 | Yeah that's my point about the practical part. I don't know that it is better at those things. I haven't tried it in that sense. In its grasp of the theoretical and the interplay of heterogeneous equipment setups, Opus is more counter-productive than productive. If you are trying to do something off the beaten path, Op... | -1 | null | null | 1,789,195,773 | batch-priority-2026-summer |
or2q447 | LocalLLaMA | 1u351b7 | or2iyb5 | 1 | dionysio211 | 1,781,199,856 | Yeah the hype is real in this field but these one shot things we are seeing aren't marketing. That's some dude in pajamas being like "Build Mario Galaxy but throw some black holes in there" and all of a sudden you realize time dilation is now a game mechanic. | -1 | null | null | 1,789,195,773 | batch-priority-2026-summer |
or2qetw | LocalLLaMA | 1u351b7 | or2q447 | 2 | No_Lingonberry1201 | 1,781,199,933 | That sounds really interesting, did you see that in a video or something? Link it if you did, please. | 0 | null | null | 1,789,195,773 | batch-priority-2026-summer |
or2re6m | LocalLLaMA | 1u351b7 | 1u351b7 | 0 | VoiceApprehensive893 | 1,781,200,188 | mythos might be agi but what it clearly isnt is an open model | 1 | null | null | 1,789,195,773 | batch-priority-2026-summer |
or2j1zm | LocalLLaMA | 1u352a0 | 1u352a0 | 0 | Velocita84 | 1,781,198,013 | Not local anthropicslop | 8 | null | null | 1,789,195,772 | batch-priority-2026-summer |
or2udx6 | LocalLLaMA | 1u36i4a | 1u36i4a | 0 | AutoModerator | 1,781,200,966 | Hello! Your post was removed as you do not have sufficient karma on r/LocalLLaMa. We are doing this in response to the large volume of spam we are unfortunately experiencing. Please participate in the sub (through comments), gain the minimum of 5 karma and then re-post
*I am a bot, and this action was performed automa... | 1 | false | /r/LocalLLaMA/comments/1u36i4a/one_config_value_makes_qwenvl_worse_and_6x_slower/or2udx6/ | 1,789,195,773 | batch-priority-2026-summer |
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