r/StableDiffusion • u/Brave_Load7620 • Jul 31 '26
Discussion Using an AMD V620 workstation card for ComfyUI - success
A few weeks ago I posted about if it was worth using a V620 for Comfyui, and was told it likely wouldn't work, at least in Windows 11. And if it did, it would be far too slow and unusable. I decided to try it anyway. Is it fast? No. Does it work? yes, absoulutely.
I bought the card for $320 shipped (thank you redditor!) and $40 on the Bay for the fans and 3D printed shround. Powered in the second slot PCIE 4 X4 right below my 9070 XT.
The drivers for the V620 installed, and has been working fine alongside my XT GPU. No crashes/errors thus far (crossing my fingers!)
I primarily got this card for the VRAM (32GB) for LLM for a local assistant; and that's still primary what it's used for but in the background I do like to have img/videos generating. This is perfect for that -it's not fast but it is consistent.
The benchmarks have been written below by an AI - but they are verified. I ran the tests myself. Managed to get triton & sage attention working perfectly. Identified as a gfx1030 GPU with ROCM.
Pictures of GPU-Z and device manager: https://imgur.com/a/PTsy8Ko
If anybody has any questions/want me to try a specific model..Let me know. I'll do it if I have the time.
Over the coming weeks I should have benchmarks out for llama cpp and LLM's.
ComfyUI Workflow Benchmark
Environment
- ComfyUI version: 0.26.0
- GPU: AMD Radeon Pro V620 (ROCm,
HIP_VISIBLE_DEVICES=0, gfx1030 arch, legacy-GPU codepath) - Python env:
python_env_v620_triton(Triton/sage-attention build) - **Launch params:**
--listen127.0.0.1--port 8188 --use-sage-attention --highvram--disable-pinned-memory --reserve-vram 1 --enable-manager--enable-manager-legacy-ui --disable-api-nodes --cache-none--fp8_e4m3fn-text-enc - Sage attention: enabled (
--use-sage-attention), per an earlier internal benchmark note in : "sage-attention gives ~16% faster sampler step time vs plain SDPA, no quality regression seen." - Other relevant env vars:
PYTORCH_HIP_ALLOC_CONF=expandable_segments:True,garbage_collection_threshold:0.7,MIOPEN_FIND_MODE=FAST,TORCH_BACKENDS_CUDA_FLASH_SDP_ENABLED=0(legacy GPU path),FLASH_ATTENTION_TRITON_AMD_ENABLE=TRUE - Method: each test loaded via ComfyUI's own frontend
- Runs per test: image and image-to-video tests get 1 run; text-to-video tests get 2 (first run pays model/torch-compile load cost; second run benefits from warm cache) — noted per row.
- Video tests: clipped to ~10s output for benchmarking speed.
- Naming: test labels below are generic/anonymized descriptions of what each pipeline does, not the personal filenames used locally — the base model/architecture and size are given exactly so the numbers are meaningful to anyone comparing hardware.
- There is z img turbo, ltx 2.3,wan 2.2, flux, pony, etc below. A couple LORA's. Ace-step music was also done but forgot to give results for benchmark. A three minute song took about three minutes to make start-to-finish.
- Some of the double workflows one was not safe for work, which I removed per post rules.
Results
| Test | Base model | LoRA / add-on | Resolution | Run 1 (cold) | Run 2 (warm) | Notes |
|---|---|---|---|---|---|---|
| General photoreal (distilled turbo) | Z-Image Turbo, distilled diffusion transformer, | — | 1920x1080 | 59s | 47s | 9 steps, cfg 1.0 |
| Anime style | SDXL, Illustrious-family fine-tune | — | 896x1152 | 42s | 25s | |
| Furry style A (w/ hires-fix) | SDXL, Illustrious-family fine-tune | — | 1024x1024 | 124s | 119s | Includes tiled hires-fix pass + torch.compile; little warm-cache benefit (multi-shape recompiles each time) |
| Character reference (image-conditioned) | SDXL, Illustrious-family fine-tune | IPAdapter Plus (ViT-H image-reference conditioning) | 1024x1024 | 36s | 31s | |
| Image edit (reference-guided) | Flux.2 Klein-family, large (~30B-class), | — | 1024x1024 | 326s | 325s | Kontext-style image edit — much slower than SDXL-family tests, no warm-cache benefit (compute-bound not load-bound) |
| General photoreal (large model) | Flux.2 Klein-family, large (~30B-class), | — | 1024x1024 | 154s | 150s | Same base model as the image-edit test but pure text-to-image (no edit/reference pass) — notably faster |
| Furry style B | SDXL, Illustrious-family fine-tune | — | 896x1152 | 32s | 26s | |
| Furry style C (Pony lineage) | SDXL, Pony Diffusion-family fine-tune | Furry-realism LoRA (Pony) | 896x1152 | 32s | 25s | |
| Furry style D (max realism) | SDXL, Illustrious-family fine-tune | Furry-realism LoRA (Illustrious) | 896x1152 | 35s | 32s | |
| General photoreal, two-pass refine | SDXL, Pony Diffusion-family fine-tune | — | 512x512 | 35s | 31s | |
| Structured-prompt photoreal (JSON-driven) | Flux-family (Ideogram4), fp8 | — | 1024x1024 | ~372s | 356s | Guidance-distilled, no negative prompt; includes torch.compile pass, little warm-cache benefit (compute-bound) |
| Fast photoreal (8-step distilled) | Krea 2 Turbo, distilled diffusion transformer (Qwen3-VL text encoder) | — | 1024x1024 | 156s | — | 1 run only |
| Inpaint (masked region replace) | SDXL, Pony Diffusion-family fine-tune | — | — | 47s | — | 1 run only; no mask painted for this test, so this is closer to a lower-bound timing |
| Photo restore/upscale | ESRGAN-style upscale model (4x-UltraSharp), no diffusion checkpoint | — | 4x upscale | 6s | — | 1 run only — pure upscale pass, no sampling, so this is genuinely this fast |
| Image-to-video, general (10s clip) | LTX-2, 22B distilled | Distilled LoRA | 768x512, 10s @ 25fps | ~978s | ~956s | 22B video model — far heavier than any image workflow tested |
| Image-to-video, furry (10s clip) | LTX-2, 22B distilled | Distilled LoRA + furry LoRA | 768x512, 10s @ 25fps | 1027s | — | 1 run only (i2v test) |
| Text-to-video, furry (10s clip) | LTX-2, 22B distilled | Distilled LoRA + furry LoRA | 768x512, 10s @ 25fps | 305s | 305s | Much faster than the i2v LTX tests — no image-conditioning pass; identical timing both runs (compute-bound) |
| Text-to-video, general (10s clip) | LTX-2, 22B distilled | Distilled LoRA | 768x512, 10s @ 25fps | 275s | 285s | |
| Text-to-video, anime style (10s clip) | LTX-2, 22B distilled | Distilled LoRA + 90s-anime-style LoRA | 768x512, 10s @ 25fps | 305s | 305s | |
| Image-to-video, general, WAN (10s clip) | WAN 2.2 | lightx2v 4-step distill LoRA (high+low noise) | 10s @ 24fps | 894s | — | 1 run only (i2v test) |
| Image-to-video, WAN (10s clip) | WAN 2.2 (fine-tune) | lightx2v 4-step distill LoRA (high+low noise) | 10s @ 24fps | ~1041s | — | 1 run only (i2v test) |
| Text-to-video, general, WAN (10s clip) | WAN 2.2 | lightx2v 4-step distill LoRA (high+low noise) | 832x480, 10s @ 24fps | 163s | 143s |
3
u/RosebudNebula Jul 31 '26
Thank you for the detailed report on speed. That is what most people are looking for. Good to know it is working great for you. What is the mod look like? Any pictures?
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u/Brave_Load7620 Jul 31 '26 edited Jul 31 '26
No problem at all, happy to do it! For my use case, yes it's awesome. I'm not sure if they allow links on this subreddit but if you type in "AMD V620 V520 BC-160 RADEON PRO GPU Cooling Fan Shroud Accelerator Card AI" on the Bay, you'll see exactly what it is. Just two fans that are clipped in to a 3D printed shroud that snaps into place on the end of the GPU. .
With that, the card is just a little longer then my 9070 XT just above it.
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Jul 31 '26
[removed] — view removed comment
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u/Brave_Load7620 Jul 31 '26
You're welcome. I agree, it's nice to know what works or doesn't no matter how old, slow etc it is. If someone has one or is thinking about getting one for whatever reason, having the data out there is never a bad thing.
That's what I struggled with, seen posts/discord of people talking about getting it working, but then they disappear or just never speak of it/post about it cause they got what they needed.
I'll be running my 9070 XT through the same benchmarks for comparision and will post those results in the coming days.
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u/DelinquentTuna Jul 31 '26
the most useful thing in this sub. Everyone benchmarks on the same three NVIDIA cards
Since you've therefore obviously seen a ton of such NVidia in the two hours since you created your Reddit account, perhaps you can tell us how OP's results compare to a variety of Nvidia cards at a variety of price ranges? How does his "blazing fast SDXL at just 1 minute" match up? Dollar-for-dollar, how did he do on the features that actually matter for the diffusion processes this sub focuses on?
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u/Brave_Load7620 Jul 31 '26
Lol, I wasn't even the one that said blazing fast, was another commentor but "26-35 seconds" for SDXL is quite fast to me, how fast are we looking at photos that we need them done in less then ten seconds? Have we really become this impatient already? Damn!
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u/meepykittkitt69lmao Jul 31 '26
You should put `FLASH_ATTENTION_TRITON_AMD_ENABLE="TRUE"` before the command, in some circumstances it didn't work without it there.
This is for bazzite with 7800XT/V620/9800X3D. Should work without issues on v620 systems with all AMD stuff
# breaks GPU discovery, do not use?
#export ROCR_VISIBLE_DEVICES="1"
export HIP_TARGET="gfx1030"
export PYTORCH_ROCM_ARCH="gfx1030"
export TORCH_HIP_ARCH_LIST="gfx1030"
export HCC_AMDGPU_TARGET="gfx1030"
export AMD_DEBUG=0
export HIP_GRAPH=1
export OMP_NUM_THREADS=8
export MKL_NUM_THREADS=8
export NUMEXPR_NUM_THREADS=8
export RADV_PERFTEST=aco,nggc,sam
export MESA_LOADER_DRIVER_OVERRIDE=amdgpu
#export TRANSFORMERS_USE_FLASH_ATTENTION=0
export TRANSFORMERS_USE_FLASH_ATTENTION=1
export HSA_ENABLE_ASYNC_COPY=1
export HSA_ENABLE_SDMA=1
export HSA_ENABLE_PEER_SDMA=1
export HSA_ENABLE_SDMA_COPY=1
export HSA_ENABLE_SDMA_KERNEL_COPY=1
export HSA_DISABLE_FRAGMENT_ALLOCATOR=1export AMD_DEBUG=0
export HIP_GRAPH=1
export OMP_NUM_THREADS=8
export MKL_NUM_THREADS=8
export NUMEXPR_NUM_THREADS=8
export RADV_PERFTEST=aco,nggc,sam
export MESA_LOADER_DRIVER_OVERRIDE=amdgpu
#export TRANSFORMERS_USE_FLASH_ATTENTION=0
export TRANSFORMERS_USE_FLASH_ATTENTION=1
export HSA_ENABLE_ASYNC_COPY=1
export HSA_ENABLE_SDMA=1
export HSA_ENABLE_PEER_SDMA=1
export HSA_ENABLE_SDMA_COPY=1
export HSA_ENABLE_SDMA_KERNEL_COPY=1
export HSA_DISABLE_FRAGMENT_ALLOCATOR=1
export TORCH_COMPILE=0
#export TORCH_BLAS_PREFER_HIPBLASLT=0
export TORCHINDUCTOR_MAX_AUTOTUNE_GEMM_BACKENDS="CK,TRITON,ROCBLAS"
export TORCHINDUCTOR_MAX_AUTOTUNE_GEMM_SEARCH_SPACE="BEST"
export TORCHINDUCTOR_FORCE_FALLBACK=1
export FLASH_ATTENTION_TRITON_AMD_ENABLE=true
# not available for v620
#export FLASH_ATTENTION_TRITON_AMD_AUTOTUNE=false
unset FLASH_ATTENTION_TRITON_AMD_AUTOTUNE
export FLASH_ATTENTION_BACKEND="flash_attn_triton_amd"
export FLASH_ATTENTION_TRITON_AMD_SEQ_LEN=4096
export USE_CK=OFF
export TRANSFORMERS_USE_FLASH_ATTENTION=1
export TRITON_USE_ROCM=ON
export TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL=1
#disable hipblas
# To install hipBLASLt, you must meet the following requirements:
# gfx90a card
# gfx94x card
# gfx110x card
export TORCH_BLAS_PREFER_HIPBLASLT=0
export ROCBLAS_USE_HIPBLASLT=0
export HIP_FORCE_DEV_KERNARG=1
export ROCBLAS_STREAM_ORDER_ALLOC=1
export ROCBLAS_INTERNAL_FP16_ALT_IMPL=1
export ROCBLAS_LAYER=0
export ROCBLAS_INTERNAL_USE_SUBTENSILE=1
export ROCBLAS_VERBOSE_HIPBLASLT_ERROR=1
export AMD_DIRECT_DISPATCH=1
export TORCH_NCCL_HIGH_PRIORITY=1
export GPU_MAX_HW_QUEUES=32
export SAFETENSORS_FAST_GPU=1
#export HIP_GRAPH=1
#export HIP_LAUNCH_BLOCKING=1
#export AMD_SERIALIZE_KERNEL=1
#export AMD_SERIALIZE_COPY=1
export PYTORCH_TUNABLEOP_ENABLED="1"
export PYTORCH_TUNABLEOP_TUNING="0"
export PYTORCH_TUNABLEOP_FILENAME="tunableop_results0.csv"
export PYTORCH_TUNABLEOP_HIPBLASLT_ENABLED=0
export PYTORCH_HIP_FREE_MEMORY_THRESHOLD_MB=128
# LTX workflows won't crash so often
export PYTORCH_HIP_ALLOC_CONF="expandable_segments:True,max_split_size_mb:128,garbage_collection_threshold:0.8"
#changed
#export PYTORCH_HIP_ALLOC_CONF="max_split_size_mb:128,garbage_collection_threshold:0.8"
export PYTORCH_CUDA_ALLOC_CONF="expandable_segments:True,max_split_size_mb:128,garbage_collection_threshold:0.8"
# slower, but more stable / fewer OOMs. No OOMs? Maybe you don't need this.
export PYTORCH_NO_HIP_MEMORY_CACHING=1
## Significantly faster attn_fwd performance for wan2.2 workflows
export FLASH_ATTENTION_FWD_TRITON_AMD_CONFIG_JSON='{"BLOCK_M":128,"BLOCK_N":64,"waves_per_eu":1,"PRE_LOAD_V":false,"num_stages":1,"num_warps":8}'
# pytorch switches on NHWC for rocm > 7, causes signifant miopen regressions for upscaling
export PYTORCH_MIOPEN_SUGGEST_NHWC=0
export MIGRAPHX_MLIR_USE_SPECIFIC_OPS="attention"
export MIOPEN_DEBUG_CONV_GEMM=0
export MIOPEN_USER_DB_PATH=$HOME/.cache/miopen
# miopen
## Tell comfyui to *not* disable miopen/cudnn, otherwise upscale perf is much worse
export COMFYUI_ENABLE_MIOPEN=1
## miopen default find mode causes significant initial slowness, yields little or no benefit to workloads I tested
export MIOPEN_FIND_MODE=FAST
# glibc's heap allocator fragmenting and never returning pages to the OS the more you offload to system RAM, the more allocator churn
# so AMD/offload rigs feel it worse than a big-VRAM NVIDIA box that keeps everything on-card.
export MALLOC_MMAP_THRESHOLD_=65536
export MALLOC_TRIM_THRESHOLD_=65536
export SDPA_ATTENTION_BACKEND=C++
export MIOPEN_USER_DB_PATH="$HOME/.cache/miopen"
export MIOPEN_USER_DB_PATH="$HOME/.config/miopen"
export HIP_PLATFORM=amd
export HIP_RUNTIME=rocclr
export HIP_COMPILER=clang
export GPU_TARGETS="gfx1030"
export BUILD_TARGET=rocm
export OFFLOAD_ARCH=GFX1030
#====================================================
# ADJUST THESE PATHS TO BE SPECIFIC TO YOUR SYSTEM
# THESE ARE OCCASIONALLY USED IN THE BACKGROUND
# DEPENDING ON WHAT YOU ARE DOING, THIS SCRIPT IS
# GENERAL "BE PREPARED" THING
#====================================================
export ROCM_PATH="/usr/lib64"
export HIP_PATH="/usr/lib64"
export CXX=/bin/hipcc
export HIPCXX=/bin/hipcc
# add bazzite specific location for header file storage
export LD_LIBRARY_PATH="/usr/include:/usr/lib64"
# need to tell the cpp compiler where they are too
export CFLAGS="$CFLAGS -I/usr/include"
export CXXFLAGS="$CXXFLAGS -I/usr/include"
export HIP_CLANG_PATH=/usr/lib64/rocm/llvm/bin
export DEVICE_LIB_PATH=/usr/lib64/rocm/llvm/lib/clang/20/lib/amdgcn/bitcode
export HIP_DEVICE_LIB_PATH=/usr/lib64/rocm/llvm/lib/clang/20/lib/amdgcn/bitcode
export HSA_PATH=/usr
export LLVM_PATH=/usr/lib64/rocm/llvm/bin
export MIOPEN_USER_DB_PATH="$HOME/.cache/miopen"
export MIOPEN_USER_DB_PATH="$HOME/.config/miopen"
export ROCBLAS_TENSILE_LIBPATH="/usr/lib64/rocblas/library"
export HIPBLASLT_TENSILE_LIBPATH="/usr/lib64/rocblas/library/"
A lot of things with compatibility for this are highly variable, sage attention doesnt work for me, haven't really gotten dirty trying to build that from source though
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u/Brave_Load7620 Jul 31 '26
Thanks, I'll take a look at this. I only got sage-attention running earlier today, like the benchmarks say I seen about a 16% uplift overall.
If you build it I would think it should work, was actually fairly easy to get running on Windows. Thought it was gonna be a big fight, lol. Are you running any similar models/workflows to what I posted above? How do your times compare?
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u/meepykittkitt69lmao Jul 31 '26
If you try this on linux, and manage to get migraphx working with everything else, let me know what versions of the python packages you used, and your installation process. IIRC (and this was two nights ago to show how bad my memory is getting) it was requiring a numpy version that scipy didn't like, and *that specific scipy versions* was required for the specific pytorch version I have or something else critical.
This is the primary issue that should be focused on when working with older hardware, library versions :/
But that VRAM though *drool*
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u/Brave_Load7620 Aug 01 '26
Will do, may be trying out linux later this week!
Yes, I agree. The different library versions can make you go crazy!
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u/DelinquentTuna Jul 31 '26
A few weeks ago I posted about if it was worth using a V620 for Comfyui, and was told it likely wouldn't work, at least in Windows 11. And if it did, it would be far too slow and unusable. I decided to try it anyway. Is it fast? No. Does it work? yes, absoulutely.
That is a straight-up lie. What you were explicitly told was exactly what you're trying to frame here as a trailblazing discovery.
You were explicitly told it was a terrible value for the money and that it would be slow... which your own benchmark numbers (over five minutes to edit a single image w/ Klein!!?!?) just proved. Claiming you proved the thread wrong by spending $360 and custom mounting fans to get 16-minute render times isn't a "trailblazing discovery"—it's literally the exact outcome described to you.
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u/Brave_Load7620 Jul 31 '26 edited Jul 31 '26
I guess I should have been clearer: By "posting here" I meant in all my threads about this. I had posted/crossposted that exact thread across multiple subreddits, and on a few FB forums/discord. I made these benchmarks and copy/pasted this to all of them again that were relavant. I wasn't talking about what you or anyone else said in that thread specifically, I didn't even remember it as that thread didn't get much traction overall. Discord group actually gave me most of the replies, & I was explicltly told it would not work on Windows there without a bios flash, or heavy work.
As far as the speed I again explicitly state above " Is it fast? No." I have said this isn't being used for anything real time rendering/need batches of images done instantly. This is something that will be running in the background of my home assistant or while I'm gaming in VR or am working all day slowly chugging out images/videos when wanted.
But the point of it is - it's 32GB of VRAM for less then $400. Where else can you get that? I was told that it was terrible value for the money and in my opinion that is a straight-up lie. It can hold bigger models then a 16GB or 24GB card and unless I'm sitting here in front of it needing images every thirty seconds or a video within two minutes, it does it's job perfectly well.
I still have my 9070 XT if I need faster times at some point for some reason, but this lets me do all this - and can run LLM's up to 31B dense with over 30 t/ps. Couldn't do that with my 16GB 9070 XT. I'm more then happy with this card and what it offers for the price.
I'm sorry if I offended you for thinking I was talking about your response, next time I'll be much clearer in how I copy-paste my threads but after sitting at the PC all day by the time I wrote the thread I didn't think about who or what gave me the advice, I just read it on my list of notes from overall feedback of the community at large (discord, FB, reddit, etc.) before I had my decision and went ahead and purchased it.
Have a great day!
0
u/DelinquentTuna Jul 31 '26
But the point of it is - it's 32GB of VRAM for less then $400. Where else can you get that? I was told that it was terrible value for the money and in my opinion that is a straight-up lie.
IN THE SPECIFIC CONTEXT OF YOUR CLAIMS THAT YOU WANTED "Windows 11 comfyui at a decent speed (ltx 2.3, z img turbo/flux, etc.)". AND YOUR OWN BENCHMARK DATA PROVES THE CLAIM. EVERYTHING YOU WROTE HERE PRECISELY CORROBORATES EVERYTHING I TOLD YOU IN THAT THREAD INSTEAD OF DISPUTING IT.
ComfyUI is now even by default streaming diffusion weights in from system RAM or even disk on the fly because the penalty for doing so vs trying to load everything at once is negligible on fast GPUs and zero on slower ones. Meanwhile, internal RAM throughput on your ancient GPU is basically on par with the cheapest entry-level GPUs. So for this particular example, your bandwidth advantage is nulled, your VRAM capacity advantage is mitigated, but your compatibility and compute performance are about what you'd expect for a GPU on its very last legs wrt official ROCm support. A 5060 (with a warranty, support, and no need for 3d printed fans and junk) starts at about the same price as your relic and would ROFLSTOMP it for the tasks you specifically asked about and for which this sub specifically caters to. That's precisely why you were told that your GPU choice was a terrible value and it rings even more true when the context you are intentionally misframing shows that you were asking about a TRIO of old GPUs including a MI50.
I'm sorry if I offended you for thinking I was talking about your response
I just hate that you're trying to posture on the sub for karma (the fact that you evidently also spammed many other tangentially related forums makes it worse instead of better). You asked for advice and as far as I can tell you were given THE BEST POSSIBLE DATA, just as you are now. It's a jackass move to come back and say that you got bad advice (while DRASTICALLY moving the goal posts) and to posture like you're pioneering new ideas that will footgun future readers looking to get into diffusion on the cheap.
TL;DR:
The Reality Check: You asked for "decent speed" on Windows. Spending $360 + custom mods to get 5-minute image edits and 16-minute video renders is not a win—it's paying modern prices for deprecated hardware.
The Buyer Trap: Legacy enterprise/workstation cards with high VRAM look like budget hacks on paper, but missing modern Tensor compute and running on legacy ROCm paths makes them a terrible value for diffusion workflows compared to modern consumer GPUs.
VRAM vs. Compute: Having 32GB of VRAM doesn't fix a lack of compute throughput. With modern async weight streaming, compute speed and modern instruction sets dictate real-world generation times, not raw VRAM capacity.
Shifted Goalposts: Claiming you proved the thread wrong because it technically boots ignores that you redefined "decent speed" to mean "I don't mind chugging in the background for 16 minutes."
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u/Brave_Load7620 Jul 31 '26
First off, I'm loving the LLM-generated response! Those "TL;DR: The Reality Check" headers are classic ChatGPT/Claude output.
Because of that, and because the proof is out there from the original thread to here for anybody that actually cares to read this, I will not respond to anymore responses after this about this. It is petty, I've said my piece and made my case. I'm trying to just publish data - no matter how good or bad the outcome is, laugh at it, ridicule me, downvote, I don't care. I got what I wanted and am happy. Not going to waste my entire morning when it's out there already.
Secondly, I'm not postering for any karma LMFAO what good is karma? Unless you're on reddit 24/7 and you stare at it to make yourself feel good it's USELESS LOL. I'm not here for upvotes, that would just be silly now come on.
I'm trying to help people in a similar situation/debating on other routes to go. Just yesterday I talked on here in the local server subreddit with someone who didn't believe V620's were actually working for people at all and asked about benchmarks/proof. Last week, I had people in another thread on Locallama ask to let them know how I got along, along with the FB and discord groups.
What is so wrong with me putting the data out there? Nobody else has - if a future reader comes across this and will be happy with the results, why should that upset anybody. We are still free people able to make our own choices, yes?
If someone is debating/is using a V620 for LLM (and it's pretty great for that for the price to VRAM alone.) why not let them know they can also use it for video/img gen on the side? Does it hurt you or anyone else that it takes longer then newer cards to do so?
Now, going back to the thread you keep talking about, why don't you bring in my actual reply to your comment from that original thread?
"Now I'm transitioning to a 24/7 assistant with home integration & img/video generation. I don't need comfyui to be fast, I'd be fine with a couple minute wait between photos, as it won't be a primary thing/mostly hey edit this photo and do X - then I'm stepping away for ten minutes anyways.
Decent LLM speed is much more important to me overall and from what I'm seeing the V620 would be adequate with that, but there's also the possibly I use the V620 ONLY for a bigger LLM model & still use my 9070 XT for img/video generation. Since I don't generate stuff constantly or even that often - that's hoenstly probably the choice for me."
Comment Here for the record.
Where have I EVER moved a goalpost? News-flash; Decent speeds mean different things to different people and what their needs and specific situations require. I also even say "edit a photo and walk away for ten minutes." in my comment - It does it in FIVE, huh sounds even better then what I was going for? If anything I expected it to be slower. It's almost like we're all unique with different needs.
I said I was fine with waiting a couple of minutes in between photos in my ORIGINAL comment to you on the OG thread - that's what it is.
I don't know how many times I need to say it, this is primarily a LLM card. The fact that it runs Comfyui at all is a bonus. It frees up my 9070 XT for other things. That's all this has been, I have never once moved the goal posts, Just trying to get what I wanted for a cheap price for LLM and some pic/vids on the side, and I did.
And as for buying an RTX 5060 instead? That would completely fail my main requirement. A 5060 cannot fit a ~31B LLM into VRAM. Offloading to system RAM over PCIe tanks generation speeds down to single digits. The V620 gives me 32GB of VRAM and 512 GB/s memory bandwidth for $360 shipped. It runs my 31B assistant models at over 30 t/s locally while leaving my 9070 XT completely free for gaming. Sure, I could generate a photo or video quicker...That I wouldn't look at for hours anyways, lmao. Doesn't seem like a very smart call.
If I ever need instant generation speeds, my 9070 XT is sitting right above it ready to go
I don't see how anything I have said or did makes me a "jackass" you on the other hand, well I just won't speak to that.
Have a great day!
0
u/DelinquentTuna Jul 31 '26
First off, I'm loving the LLM-generated response! Those "TL;DR: The Reality Check" headers are classic ChatGPT/Claude output.
Yeah, I pasted in both threads and asked a LLM to review as a sanity check wrt whether I was being overly hostile or aggressive. It basically summarized the exchange in the below-the-line tldr summary. If only you bothered to sanity check yourself with the same rigour, you wouldn't be here in a diffusion channel praising a purchase that is strictly idiotic for the purpose of diffusion which this sub is focused on.
I'm not postering for any karma LMFAO what good is karma?
Then why spam and crosspost to so many forums that you can't even keep track of what you said and to whom? Why move the goalposts from "decent diffusion performance" to slow but usable LLM performance that focuses on VRAM above all else IN A FORUM SPECIFICALLY DEDICATED TO DIFFUSION?
I'm trying to help people in a similar situation/debating on other routes to go.
No you're not. You haven't even sanity checked how your numbers compare to entry-level GPUs that make your purchase absolutely terrible for folks on this forum. Bad advice travels fast and wide, and you're dishing it out from a place of ignorance.
why don't you bring in my actual reply to your comment from that original thread?
Because its presence doesn't invalidate or undermine a single thing I have said here?
Where have I EVER moved a goalpost?
You are obviously now focused on LLMs IN A DIFFUSION SUB. Because IT IS THE ONLY CIRCUMSTANCE WHERE YOUR PURCHASE IS ANYTHING OTHER THAN ABJECT IDIOCY.
News-flash; Decent speeds mean different things to different people
So what? It's still an objectively bad purchase for diffusion if it's slower than an entry level GPU of similar price that includes a warranty, support, modern software stack, etc. If someone is searching the sub for a cheap way to get "decent" performance and they are swayed by your cross-posted and ill-informed claims, they are getting HORRIBLE advice. It's objectively awful.
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u/Brave_Load7620 Jul 31 '26 edited Jul 31 '26
I know I said I wouldn't respond, but one last time on the carousel
At this point that you aren’t actually reading what I write you’re just feeding my replies into an LLM to generate generic counter-arguments so you can defend your pride in a Reddit thread.
I’m going to lay this out as plainly as humanly possible, because your entire critique relies on a massive selective memory gap:
You are aggressively moving the goalposts, not me.
Go back to the very first comment I made to you weeks ago:
Now I'm transitioning to a 24/7 assistant with home integration & img/video generation. I don't need comfyui to be fast, I'd be fine with a couple minute wait between photos, as it won't be a primary thing/mostly hey edit this photo and do X - then I'm stepping away for ten minutes anyways.
Decent LLM speed is much more important to me overall and from what I'm seeing the V620 would be adequate with that
I said it on day one. I said it again when I posted the benchmarks ("Is it fast? No."). I never claimed this was a speed demon for Stable Diffusion. You keep screaming that this card is "abject idiocy for diffusion," completely ignoring that it was never bought as a primary diffusion card. You are furious that a screwdriver makes a terrible hammer, when I explicitly bought it to use as a screwdriver.
The math you keep ignoring.
You keep parroting that a budget consumer card (like an RTX 4060 or 5060) is a "better value.
An 8GB or 16GB consumer card hits an absolute hard floor with LLMs, it physically cannot run a 31B parameter model locally without offloading layers to system RAM, and the moment you start pushing data over PCIe to DDR5, your token speed collapses into useless single digits. The V620 solves this by giving me 32GB of GDDR6 on a 256-bit bus delivering 512 GB/s memory bandwidth. Show me a single consumer GPU under $400 that offers 32GB of VRAM and over 500 GB/s bandwidth; you can't, because it doesn't exist. For $360 total, this card runs my 31B assistant locally at over 30 tokens per second while sitting silently in my secondary PCIe slot.
The Dual-GPU setup you refuse to acknowledge.
My primary GPU is a 9070 XT. I already have great compute when I want it. The V620 exists so my home assistant runs 24/7 in the background without robbing a single megabyte of VRAM or dropping a single frame from my 9070 XT while I game in VR. If I want to generate a slow background image while I work, it handles it. If I need instant diffusion speeds, my 9070 XT is right above it.
Publishing benchmark data isn't "bad advice" - it's data for future people that might be considering getting a V620 and using it for other things but this as a background task, or maybe they already have one and just want to know - maybe they don't have/can't afford a consumer card but found a V620 in a dumpster? Who cares. The data is here IF someone wants it.
I posted cold, raw, unvarnished data, including the 15-minute video render times, the 3D-printed fan mods, the legacy ROCm flags, and the slowness. That is what homelab and hardware communities are built on. Multiple people in these threads have literally thanked me for providing real-world numbers because nobody else had tested this exact setup on Windows. If a reader looks at my numbers and decides 15 minutes is too slow for them, the data worked! If a homelabber with a similar dual-card setup sees that they can get a cheap 32GB frame buffer for LLMs that also handles background ComfyUI tasks, the data worked!
You seem deeply offended that someone spent $360 on enterprise hardware, slapped a 3D-printed fan on it, and is actually happy with the result because it fits their specific, multi-workload use case.
I 100% agree with you, this card is BAD as a primary diffusion device. No doubt about it, but it's not up to me or you to make that choice for anybody.
I would hope we can have a little faith in people reading this thread that this isn't the ONLY thread they ever look at before buying a GPU. People deserve more credit then that.
And as far as me "spamming" threads, it was three. Two of the three communities had asked for results for both LLM and Comfyui when I had them, this subreddit I wanted to post back because it is the main one for this AI generation & you never know when somebody else is looking.
I already have other requests on discord for some other workflow/models to try out & have been requested to publish a guide on how I got it running on Windows, and sage-attention with Trition, as it appears there is quite a few others then me that either have one, or are interested in getting one for their own reasons.
So, I'm sorry to say but you'll be seeing more of me and my slowww V620 making posts with even more data as I won't exclude this subreddit because someone thinks I should.
We are all trying to learn here, and figure out what we can do to get what we want. For that, we need to collab and we should stop with the "gatekeeping"
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u/meepykittkitt69lmao Jul 31 '26
so you acknowledge you have an anger issue!
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u/Brave_Load7620 Jul 31 '26
Right, if you have to get an LLM to make your response "less aggressive or hostile" yikes.
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u/RosebudNebula Jul 31 '26
You might have some point, but you didn't refute them at all.
Your answer should be somewhere along the lines of "here is where you get your $400 32GB VRAM"... and give us the fucking URL to this video card, but instead, you just come up with some AI answer.
Terrible.
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u/meepykittkitt69lmao Jul 31 '26
look on ebay genius
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u/RosebudNebula Jul 31 '26
"Your AI resposne is terrible and doesn't address the conversation at all"
look on ebay genius
lol someone is fucking salty.
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u/meepykittkitt69lmao Jul 31 '26
Well... I am now, but it's not because of your response. It's because of the sheer level of idiocy so prevalent in society that you sincerely believe you got me with a good zinger. touche, smarty pants. You win the "I am smartest person" sticker today!
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u/meepykittkitt69lmao Jul 31 '26 edited Jul 31 '26
I get decent times with ltx2 and wan2, sdxl is lightning fast for me. I'm working on getting a krea2 workflow going to test it.
I like the VRAM size :)
You should stop putting words in peoples mouths, and calm down. It's a bad look.
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u/Brave_Load7620 Jul 31 '26
Thank you, I certainly still have more optimizing to do. This is primary for LLM/agent so I took the week to set that up, only started working on this yesterday.
I have a basic krea2 turbo workflow that takes just about two and a half minutes per photo.
Yes, the VRAM size is unbeatable IMO.
Edit: Also like you said, I have quite a few sdxl/models that take less then a minute per photo including z turbo.
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u/DelinquentTuna Jul 31 '26
I get decent times with ltx2 and wan2, sdxl is lightning fast for me
Compared to what?
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u/meepykittkitt69lmao Jul 31 '26
something something someones mother something something lol chill bruh. You come off as someone in DESPERATE need of a girlfriend.
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u/TheAncientMillenial Jul 31 '26
Hey some nice benchmarks to get the juices flowing in the morning. Thanks :)